Agentic Data Engineer
ClassLink · United States · 3 wk ago
RemoteRemoteDesignFull-time
We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes description about company, role, responsibilities, required skills, preferred, benefits. No explicit Pay or Schedule beyond "This role is remote with quarterly in-person strategy meetings." That's schedule info: remote with quarterly in-person meetings. That is schedule info. So we can include Schedule section with that content. Pay not mentioned, so omit Pay.
We need headings for each section. Use
for each section. Use - for lists. Use
for prose.
We must not repeat job title as heading. No Job ID.
We must preserve all substantive information; do not invent or summarize away detail. Must not include boilerplate like EEO etc. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions.
We need to extract substantive content: company mission paragraph, values, role description, responsibilities (list), required skills (list), preferred (list), benefits (list), schedule (remote with quarterly in-person). Also maybe "About the role" could be the initial paragraph describing role? The instruction: Use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to decide which sections to include.
We have:
- About the role: could be the paragraph describing the role: "ClassLink is seeking an Agentic Data Engineer, IC2. This role designs, builds, and maintains scalable data platforms, pipelines, integrations, APIs, and cloud-native services supporting ClassLink’s products, analytics, and AI-powered applications. Working across engineering teams, this role develops secure, reliable data solutions and contributes to automation, data quality, governance, reusable frameworks, and engineering best practices. Success requires strong data engineering and cloud expertise, analytical problem-solving, collaboration, and a continuous improvement mindset."
That seems appropriate for About the role.
- Responsibilities: list of bullet points under "Key Responsibilities" with subheadings AI-Enabled Data engineering & Technical Excellence, Accountability & Results, Operational Excellence & Continuous Improvement, Collaboration & Communication. We need to flatten into a list? The instruction: Use - for any list of duties/requirements/benefits. So we can create a
with each duty as - . Should we preserve subheadings? Probably not needed; just list duties. But we must preserve ALL substantive information; not invent or summarize away detail. If we flatten, we might lose grouping but still preserve each duty. Could also keep subheadings as
then list. But instruction says use
- for any list of duties/requirements/benefits. So we can have a
intro then
. That's fine.
- Requirements: likely the "Required Skills:" list. That's a list of required skills. Could be Requirements section.
- Qualifications: maybe education/experience? Could be part of Required Skills. But we have separate sections: Requirements, Qualifications, Skills. The posting lumps required skills (education, experience, technical). Could treat Requirements as the list of required skills (including education, experience). Qualifications maybe not separate; but we could put education/experience under Qualifications. However we must not create empty sections. We need to decide.
We have: Required Skills: bullet list includes education, experience, technical proficiencies. Preferred: another list.
We could map:
- About the role: prose description.
- Responsibilities: list of duties.
- Requirements: list of required skills (including education, experience, technical).
- Qualifications: maybe we could omit if no distinct content besides required? But we have "Preferred:" which could be Qualifications or Skills. The instruction includes Qualifications as a possible heading. We could put "Preferred" under Qualifications. Or we could put "Skills" for technical skills, and "Qualifications" for education/experience. But we need to avoid thin sections.
Better: Use sections: About the role, Responsibilities, Requirements (required skills), Qualifications (preferred), Benefits, Schedule.
Skills section maybe redundant; we could omit Skills if we put technical skills under Requirements. But we have both required and preferred technical skills. Could put all technical skills under Skills, and education/experience under Requirements. However the instruction says prefer a few substantive sections over many thin ones. So maybe combine.
Let's think: The posting includes:
- Required Skills: education, experience, Python, SQLAlchemy, REST APIs, ETL/ELT, AWS, Git, CI/CD, analytical, communication, AI-assisted tools.
- Preferred: multi-tenant SaaS, Snowflake, data orchestration, event-driven, vector databases/RAG, IaC/containerization/K8s, mentoring, data governance, AWS certifications.
We could have:
- Requirements: education + experience + mandatory technical skills (the Required Skills list).
- Qualifications: preferred qualifications (the Preferred list).
- Skills: maybe not needed.
But we have both Required and Preferred; we could treat Required as Requirements, Preferred as Qualifications. That seems logical.
Thus sections:
About the role
...
Responsibilities
- ...
...
Requirements
- ...
...
(list required skills)
Qualifications
- ...
...
(list preferred)
Benefits
- ...
...
Schedule
This role is remote with quarterly in-person strategy meetings.
We must not include Pay.
Now we need to extract the exact sentences/bullets without adding or omitting.
Let's copy the About the role paragraph exactly:
"ClassLink is seeking an Agentic Data Engineer, IC2. This role designs, builds, and maintains scalable data platforms, pipelines, integrations, APIs, and cloud-native services supporting ClassLink’s products, analytics, and AI-powered applications. Working across engineering teams, this role develops secure, reliable data solutions and contributes to automation, data quality, governance, reusable frameworks, and engineering best practices. Success requires strong data engineering and cloud expertise, analytical problem-solving, collaboration, and a continuous improvement mindset."
Check for any extra fluff: That's it.
Now Responsibilities: We need to list each duty from the "Key Responsibilities" section.
The section includes headings: AI-Enabled Data engineering & Technical Excellence, Accountability & Results, Operational Excellence & Continuous Improvement, Collaboration & Communication. Under each heading there are sentences.
We need to extract each duty as a separate - . Let's parse:
Under AI-Enabled Data engineering & Technical Excellence:
- "Design, develop, and optimize scalable data pipelines, REST APIs, and cloud-native data services that support ClassLink products and internal platforms."
- "Apply AI-assisted engineering practices, modern data engineering methodologies, and established coding standards to improve engineering effectiveness, solution quality, and developer productivity."
- "Ensure data engineering solutions comply with established standards for security, testing, observability, data quality, and software reliability."
Under Accountability & Results:
- "Own technical implementation for assigned data engineering initiatives from design through deployment."
- "Design and enhance multi-tenant data architectures that provide secure, scalable, and reliable customer data processing."
- "Develop and extend ETL/ELT pipelines by integrating new vendor data sources through REST APIs, SFTP, event-driven integrations, message queues, and other supported data exchange methods."
- "Design scalable REST APIs and database solutions that support application functionality, reporting, and downstream integrations."
- "Extend relational data models, implement schema migrations, and optimize database performance while maintaining data integrity."
Under Operational Excellence & Continuous Improvement:
- "Improve engineering efficiency through automation, workflow optimization, testing improvements, and AI-assisted development practices."
- "Develop and maintain automated testing for APIs, ETL processes, and data validation to improve release confidence and data quality."
- "Contribute reusable components, technical documentation, engineering standards, and operational runbooks that improve consistency across teams."
- "Support and optimize AWS-based data platforms through automation, monitoring, observability, performance tuning, and cost optimization while identifying opportunities to improve scalability, reliability, and operational efficiency."
Under Collaboration & Communication:
- "Collaborate with Product Management, Agentic Engineering, Cloud Engineering, Security Engineering, Quality Engineering, Architecture, Infrastructure, Analytics, and fellow Agentic Data Engineers to deliver reliable, scalable, and secure data solutions."
- "Participate in technical design discussions, code reviews, architecture reviews, and engineering working groups."
- "Share technical knowledge and mentor Associate Data Engineers through collaborative problem-solving, design guidance, and code reviews."
Also there is a line: "This role is remote with quarterly in-person strategy meetings." That's schedule.
Now Required Skills list:
"Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related field, or equivalent combination of education and experience.
3–5 years of experience in data engineering, backend software engineering, or cloud-based data platform development.
Advanced proficiency in Python, including object-oriented programming, type hinting, decorators, context managers, and asynchronous programming concepts.
Strong experience with SQLAlchemy ORM, Alembic migrations, relational database design, and PostgreSQL.
Experience designing, developing, testing, and supporting REST APIs using FastAPI or similar frameworks.
Experience designing and supporting ETL/ELT pipelines and integrating data from APIs, SFTP, vendor systems, and other external sources.
Experience designing and supporting AWS cloud services and cloud-native data solutions, including storage, compute, networking, monitoring, and serverless capabilities.
Experience with Git, CI/CD pipelines, automated testing, observability, and Agile software development.
Strong analytical, troubleshooting, and problem-solving skills with the ability to independently resolve complex technical issues.
Excellent communication and collaboration skills with experience working on cross-functional Agile teams.
Experience using AI-assisted software development tools and modern engineering practices to improve developer productivity and software quality."
We need to put each as
- . Ensure we keep the exact phrasing.
Preferred list:
"Experience designing and supporting multi-tenant SaaS platforms.
Experience with Snowflake or other cloud data warehouse technologies.
Experience with data orchestration platforms and workflow automation tools.
Experience building scalable event-driven or distributed data processing systems.
Experience designing or supporting vector databases, Retrieval-Augmented Generation (RAG) pipelines, semantic search, feature stores, or other AI-ready data architectures.
Familiarity with Infrastructure as Code, containerization, Kubernetes, or serverless architectures.
Experience mentoring junior engineers or leading technical initiatives.
Knowledge of data governance, data quality frameworks, observability, and monitoring practices.
Experience using AI-assisted development tools to improve software engineering productivity.
AWS certifications or data engineering certifications."
Now Benefits list:
"Generous Paid Time Off: 4+ weeks of vacation and 13+ paid holidays
Parental Leave: 12 weeks fully paid for all parents
Retirement: 401(k) with 0.5:1 company match
Comprehensive Health Coverage: Medical, dental, and vision plans
Insurance: Company-paid life, short-term disability, and long-term disability, plus voluntary options including supplemental life, accident, and pet insurance
Perks:
Volunteer Time Off: Give back through ClassLink Cares paid volunteer days
Lifelong Learning: Tuition reimbursement for continued education
Growth & Development: Coaching and internal programs to support career and personal growth
Supportive Culture: A workplace that values curiosity, compassion, and continuous learning
Connection & Community: Annual company retreats and team events with bright, fun coworkers"
We need to format as list items. The "Perks:" line is a heading inside benefits; we could treat each perk as separate list items. The instruction: Use
- for any list of duties/requirements/benefits. So we can just list each benefit/perk as
- . We'll keep the exact text.
We should not include the heading "Perks:" as a separate list item? It's part of the benefits
for prose. We must not repeat job title as heading. No Job ID. We must preserve all substantive information; do not invent or summarize away detail. Must not include boilerplate like EEO etc. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. We need to extract substantive content: company mission paragraph, values, role description, responsibilities (list), required skills (list), preferred (list), benefits (list), schedule (remote with quarterly in-person). Also maybe "About the role" could be the initial paragraph describing role? The instruction: Use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to decide which sections to include.
We have:
- About the role: could be the paragraph describing the role: "ClassLink is seeking an Agentic Data Engineer, IC2. This role designs, builds, and maintains scalable data platforms, pipelines, integrations, APIs, and cloud-native services supporting ClassLink’s products, analytics, and AI-powered applications. Working across engineering teams, this role develops secure, reliable data solutions and contributes to automation, data quality, governance, reusable frameworks, and engineering best practices. Success requires strong data engineering and cloud expertise, analytical problem-solving, collaboration, and a continuous improvement mindset."
That seems appropriate for About the role.
- Responsibilities: list of bullet points under "Key Responsibilities" with subheadings AI-Enabled Data engineering & Technical Excellence, Accountability & Results, Operational Excellence & Continuous Improvement, Collaboration & Communication. We need to flatten into a list? The instruction: Use - for any list of duties/requirements/benefits. So we can create a
with each duty as - . Should we preserve subheadings? Probably not needed; just list duties. But we must preserve ALL substantive information; not invent or summarize away detail. If we flatten, we might lose grouping but still preserve each duty. Could also keep subheadings as
then list. But instruction says use
- for any list of duties/requirements/benefits. So we can have a
intro then
. That's fine.
- Requirements: likely the "Required Skills:" list. That's a list of required skills. Could be Requirements section.
- Qualifications: maybe education/experience? Could be part of Required Skills. But we have separate sections: Requirements, Qualifications, Skills. The posting lumps required skills (education, experience, technical). Could treat Requirements as the list of required skills (including education, experience). Qualifications maybe not separate; but we could put education/experience under Qualifications. However we must not create empty sections. We need to decide.
We have: Required Skills: bullet list includes education, experience, technical proficiencies. Preferred: another list.
We could map:
- About the role: prose description.
- Responsibilities: list of duties.
- Requirements: list of required skills (including education, experience, technical).
- Qualifications: maybe we could omit if no distinct content besides required? But we have "Preferred:" which could be Qualifications or Skills. The instruction includes Qualifications as a possible heading. We could put "Preferred" under Qualifications. Or we could put "Skills" for technical skills, and "Qualifications" for education/experience. But we need to avoid thin sections.
Better: Use sections: About the role, Responsibilities, Requirements (required skills), Qualifications (preferred), Benefits, Schedule.
Skills section maybe redundant; we could omit Skills if we put technical skills under Requirements. But we have both required and preferred technical skills. Could put all technical skills under Skills, and education/experience under Requirements. However the instruction says prefer a few substantive sections over many thin ones. So maybe combine.
Let's think: The posting includes:
- Required Skills: education, experience, Python, SQLAlchemy, REST APIs, ETL/ELT, AWS, Git, CI/CD, analytical, communication, AI-assisted tools.
- Preferred: multi-tenant SaaS, Snowflake, data orchestration, event-driven, vector databases/RAG, IaC/containerization/K8s, mentoring, data governance, AWS certifications.
We could have:
- Requirements: education + experience + mandatory technical skills (the Required Skills list).
- Qualifications: preferred qualifications (the Preferred list).
- Skills: maybe not needed.
But we have both Required and Preferred; we could treat Required as Requirements, Preferred as Qualifications. That seems logical.
Thus sections:
About the role
...
Responsibilities
- ...
...
Requirements
- ...
...
(list required skills)
Qualifications
- ...
...
(list preferred)
Benefits
- ...
...
Schedule
This role is remote with quarterly in-person strategy meetings.
We must not include Pay.
Now we need to extract the exact sentences/bullets without adding or omitting.
Let's copy the About the role paragraph exactly:
"ClassLink is seeking an Agentic Data Engineer, IC2. This role designs, builds, and maintains scalable data platforms, pipelines, integrations, APIs, and cloud-native services supporting ClassLink’s products, analytics, and AI-powered applications. Working across engineering teams, this role develops secure, reliable data solutions and contributes to automation, data quality, governance, reusable frameworks, and engineering best practices. Success requires strong data engineering and cloud expertise, analytical problem-solving, collaboration, and a continuous improvement mindset."
Check for any extra fluff: That's it.
Now Responsibilities: We need to list each duty from the "Key Responsibilities" section.
The section includes headings: AI-Enabled Data engineering & Technical Excellence, Accountability & Results, Operational Excellence & Continuous Improvement, Collaboration & Communication. Under each heading there are sentences.
We need to extract each duty as a separate - . Let's parse:
Under AI-Enabled Data engineering & Technical Excellence:
- "Design, develop, and optimize scalable data pipelines, REST APIs, and cloud-native data services that support ClassLink products and internal platforms."
- "Apply AI-assisted engineering practices, modern data engineering methodologies, and established coding standards to improve engineering effectiveness, solution quality, and developer productivity."
- "Ensure data engineering solutions comply with established standards for security, testing, observability, data quality, and software reliability."
Under Accountability & Results:
- "Own technical implementation for assigned data engineering initiatives from design through deployment."
- "Design and enhance multi-tenant data architectures that provide secure, scalable, and reliable customer data processing."
- "Develop and extend ETL/ELT pipelines by integrating new vendor data sources through REST APIs, SFTP, event-driven integrations, message queues, and other supported data exchange methods."
- "Design scalable REST APIs and database solutions that support application functionality, reporting, and downstream integrations."
- "Extend relational data models, implement schema migrations, and optimize database performance while maintaining data integrity."
Under Operational Excellence & Continuous Improvement:
- "Improve engineering efficiency through automation, workflow optimization, testing improvements, and AI-assisted development practices."
- "Develop and maintain automated testing for APIs, ETL processes, and data validation to improve release confidence and data quality."
- "Contribute reusable components, technical documentation, engineering standards, and operational runbooks that improve consistency across teams."
- "Support and optimize AWS-based data platforms through automation, monitoring, observability, performance tuning, and cost optimization while identifying opportunities to improve scalability, reliability, and operational efficiency."
Under Collaboration & Communication:
- "Collaborate with Product Management, Agentic Engineering, Cloud Engineering, Security Engineering, Quality Engineering, Architecture, Infrastructure, Analytics, and fellow Agentic Data Engineers to deliver reliable, scalable, and secure data solutions."
- "Participate in technical design discussions, code reviews, architecture reviews, and engineering working groups."
- "Share technical knowledge and mentor Associate Data Engineers through collaborative problem-solving, design guidance, and code reviews."
Also there is a line: "This role is remote with quarterly in-person strategy meetings." That's schedule.
Now Required Skills list:
"Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related field, or equivalent combination of education and experience.
3–5 years of experience in data engineering, backend software engineering, or cloud-based data platform development.
Advanced proficiency in Python, including object-oriented programming, type hinting, decorators, context managers, and asynchronous programming concepts.
Strong experience with SQLAlchemy ORM, Alembic migrations, relational database design, and PostgreSQL.
Experience designing, developing, testing, and supporting REST APIs using FastAPI or similar frameworks.
Experience designing and supporting ETL/ELT pipelines and integrating data from APIs, SFTP, vendor systems, and other external sources.
Experience designing and supporting AWS cloud services and cloud-native data solutions, including storage, compute, networking, monitoring, and serverless capabilities.
Experience with Git, CI/CD pipelines, automated testing, observability, and Agile software development.
Strong analytical, troubleshooting, and problem-solving skills with the ability to independently resolve complex technical issues.
Excellent communication and collaboration skills with experience working on cross-functional Agile teams.
Experience using AI-assisted software development tools and modern engineering practices to improve developer productivity and software quality."
We need to put each as
- . Ensure we keep the exact phrasing.
Preferred list:
"Experience designing and supporting multi-tenant SaaS platforms.
Experience with Snowflake or other cloud data warehouse technologies.
Experience with data orchestration platforms and workflow automation tools.
Experience building scalable event-driven or distributed data processing systems.
Experience designing or supporting vector databases, Retrieval-Augmented Generation (RAG) pipelines, semantic search, feature stores, or other AI-ready data architectures.
Familiarity with Infrastructure as Code, containerization, Kubernetes, or serverless architectures.
Experience mentoring junior engineers or leading technical initiatives.
Knowledge of data governance, data quality frameworks, observability, and monitoring practices.
Experience using AI-assisted development tools to improve software engineering productivity.
AWS certifications or data engineering certifications."
Now Benefits list:
"Generous Paid Time Off: 4+ weeks of vacation and 13+ paid holidays
Parental Leave: 12 weeks fully paid for all parents
Retirement: 401(k) with 0.5:1 company match
Comprehensive Health Coverage: Medical, dental, and vision plans
Insurance: Company-paid life, short-term disability, and long-term disability, plus voluntary options including supplemental life, accident, and pet insurance
Perks:
Volunteer Time Off: Give back through ClassLink Cares paid volunteer days
Lifelong Learning: Tuition reimbursement for continued education
Growth & Development: Coaching and internal programs to support career and personal growth
Supportive Culture: A workplace that values curiosity, compassion, and continuous learning
Connection & Community: Annual company retreats and team events with bright, fun coworkers"
We need to format as list items. The "Perks:" line is a heading inside benefits; we could treat each perk as separate list items. The instruction: Use
- for any list of duties/requirements/benefits. So we can just list each benefit/perk as
- . We'll keep the exact text.
We should not include the heading "Perks:" as a separate list item? It's part of the benefits
- with each duty as
- . Should we preserve subheadings? Probably not needed; just list duties. But we must preserve ALL substantive information; not invent or summarize away detail. If we flatten, we might lose grouping but still preserve each duty. Could also keep subheadings as
then list. But instruction says use
- for any list of duties/requirements/benefits. So we can have a
intro then
- . That's fine.
- Requirements: likely the "Required Skills:" list. That's a list of required skills. Could be Requirements section.
- Qualifications: maybe education/experience? Could be part of Required Skills. But we have separate sections: Requirements, Qualifications, Skills. The posting lumps required skills (education, experience, technical). Could treat Requirements as the list of required skills (including education, experience). Qualifications maybe not separate; but we could put education/experience under Qualifications. However we must not create empty sections. We need to decide.
We have: Required Skills: bullet list includes education, experience, technical proficiencies. Preferred: another list.
We could map:
- About the role: prose description.
- Responsibilities: list of duties.
- Requirements: list of required skills (including education, experience, technical).
- Qualifications: maybe we could omit if no distinct content besides required? But we have "Preferred:" which could be Qualifications or Skills. The instruction includes Qualifications as a possible heading. We could put "Preferred" under Qualifications. Or we could put "Skills" for technical skills, and "Qualifications" for education/experience. But we need to avoid thin sections.
Better: Use sections: About the role, Responsibilities, Requirements (required skills), Qualifications (preferred), Benefits, Schedule.
Skills section maybe redundant; we could omit Skills if we put technical skills under Requirements. But we have both required and preferred technical skills. Could put all technical skills under Skills, and education/experience under Requirements. However the instruction says prefer a few substantive sections over many thin ones. So maybe combine.
Let's think: The posting includes:
- Required Skills: education, experience, Python, SQLAlchemy, REST APIs, ETL/ELT, AWS, Git, CI/CD, analytical, communication, AI-assisted tools.
- Preferred: multi-tenant SaaS, Snowflake, data orchestration, event-driven, vector databases/RAG, IaC/containerization/K8s, mentoring, data governance, AWS certifications.
We could have:
- Requirements: education + experience + mandatory technical skills (the Required Skills list).
- Qualifications: preferred qualifications (the Preferred list).
- Skills: maybe not needed.
But we have both Required and Preferred; we could treat Required as Requirements, Preferred as Qualifications. That seems logical.
Thus sections:
- ... ...
- ... ...
- ... ...
- ... ...
- . Let's parse: Under AI-Enabled Data engineering & Technical Excellence: - "Design, develop, and optimize scalable data pipelines, REST APIs, and cloud-native data services that support ClassLink products and internal platforms." - "Apply AI-assisted engineering practices, modern data engineering methodologies, and established coding standards to improve engineering effectiveness, solution quality, and developer productivity." - "Ensure data engineering solutions comply with established standards for security, testing, observability, data quality, and software reliability." Under Accountability & Results: - "Own technical implementation for assigned data engineering initiatives from design through deployment." - "Design and enhance multi-tenant data architectures that provide secure, scalable, and reliable customer data processing." - "Develop and extend ETL/ELT pipelines by integrating new vendor data sources through REST APIs, SFTP, event-driven integrations, message queues, and other supported data exchange methods." - "Design scalable REST APIs and database solutions that support application functionality, reporting, and downstream integrations." - "Extend relational data models, implement schema migrations, and optimize database performance while maintaining data integrity." Under Operational Excellence & Continuous Improvement: - "Improve engineering efficiency through automation, workflow optimization, testing improvements, and AI-assisted development practices." - "Develop and maintain automated testing for APIs, ETL processes, and data validation to improve release confidence and data quality." - "Contribute reusable components, technical documentation, engineering standards, and operational runbooks that improve consistency across teams." - "Support and optimize AWS-based data platforms through automation, monitoring, observability, performance tuning, and cost optimization while identifying opportunities to improve scalability, reliability, and operational efficiency." Under Collaboration & Communication: - "Collaborate with Product Management, Agentic Engineering, Cloud Engineering, Security Engineering, Quality Engineering, Architecture, Infrastructure, Analytics, and fellow Agentic Data Engineers to deliver reliable, scalable, and secure data solutions." - "Participate in technical design discussions, code reviews, architecture reviews, and engineering working groups." - "Share technical knowledge and mentor Associate Data Engineers through collaborative problem-solving, design guidance, and code reviews." Also there is a line: "This role is remote with quarterly in-person strategy meetings." That's schedule. Now Required Skills list: "Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related field, or equivalent combination of education and experience. 3–5 years of experience in data engineering, backend software engineering, or cloud-based data platform development. Advanced proficiency in Python, including object-oriented programming, type hinting, decorators, context managers, and asynchronous programming concepts. Strong experience with SQLAlchemy ORM, Alembic migrations, relational database design, and PostgreSQL. Experience designing, developing, testing, and supporting REST APIs using FastAPI or similar frameworks. Experience designing and supporting ETL/ELT pipelines and integrating data from APIs, SFTP, vendor systems, and other external sources. Experience designing and supporting AWS cloud services and cloud-native data solutions, including storage, compute, networking, monitoring, and serverless capabilities. Experience with Git, CI/CD pipelines, automated testing, observability, and Agile software development. Strong analytical, troubleshooting, and problem-solving skills with the ability to independently resolve complex technical issues. Excellent communication and collaboration skills with experience working on cross-functional Agile teams. Experience using AI-assisted software development tools and modern engineering practices to improve developer productivity and software quality." We need to put each as
- . Ensure we keep the exact phrasing.
Preferred list:
"Experience designing and supporting multi-tenant SaaS platforms.
Experience with Snowflake or other cloud data warehouse technologies.
Experience with data orchestration platforms and workflow automation tools.
Experience building scalable event-driven or distributed data processing systems.
Experience designing or supporting vector databases, Retrieval-Augmented Generation (RAG) pipelines, semantic search, feature stores, or other AI-ready data architectures.
Familiarity with Infrastructure as Code, containerization, Kubernetes, or serverless architectures.
Experience mentoring junior engineers or leading technical initiatives.
Knowledge of data governance, data quality frameworks, observability, and monitoring practices.
Experience using AI-assisted development tools to improve software engineering productivity.
AWS certifications or data engineering certifications."
Now Benefits list:
"Generous Paid Time Off: 4+ weeks of vacation and 13+ paid holidays
Parental Leave: 12 weeks fully paid for all parents
Retirement: 401(k) with 0.5:1 company match
Comprehensive Health Coverage: Medical, dental, and vision plans
Insurance: Company-paid life, short-term disability, and long-term disability, plus voluntary options including supplemental life, accident, and pet insurance
Perks:
Volunteer Time Off: Give back through ClassLink Cares paid volunteer days
Lifelong Learning: Tuition reimbursement for continued education
Growth & Development: Coaching and internal programs to support career and personal growth
Supportive Culture: A workplace that values curiosity, compassion, and continuous learning
Connection & Community: Annual company retreats and team events with bright, fun coworkers"
We need to format as list items. The "Perks:" line is a heading inside benefits; we could treat each perk as separate list items. The instruction: Use
- for any list of duties/requirements/benefits. So we can just list each benefit/perk as
- . We'll keep the exact text. We should not include the heading "Perks:" as a separate list item? It's part of the benefits
About the role
...
Responsibilities
Requirements
Qualifications
Benefits
Schedule
This role is remote with quarterly in-person strategy meetings.
We must not include Pay. Now we need to extract the exact sentences/bullets without adding or omitting. Let's copy the About the role paragraph exactly: "ClassLink is seeking an Agentic Data Engineer, IC2. This role designs, builds, and maintains scalable data platforms, pipelines, integrations, APIs, and cloud-native services supporting ClassLink’s products, analytics, and AI-powered applications. Working across engineering teams, this role develops secure, reliable data solutions and contributes to automation, data quality, governance, reusable frameworks, and engineering best practices. Success requires strong data engineering and cloud expertise, analytical problem-solving, collaboration, and a continuous improvement mindset." Check for any extra fluff: That's it. Now Responsibilities: We need to list each duty from the "Key Responsibilities" section. The section includes headings: AI-Enabled Data engineering & Technical Excellence, Accountability & Results, Operational Excellence & Continuous Improvement, Collaboration & Communication. Under each heading there are sentences. We need to extract each duty as a separate
- for any list of duties/requirements/benefits. So we can have a