Senior Data Engineer

We need to output only HTML fragment, no html/body tags, no markdown fences. Use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where posting has real specific content. We need to extract content. Given posting: Role: Senior Data Engineer Consultant Position Type: Contract Location: Oklahoma City Pay Rate Range: Open, Based on Experience Benefits: You are eligible for medical, dental, vision insurance benefits, 401K Then some intro paragraphs: "Are you looking for a growth opportunity..." etc. Overview: description. Key Responsibilities: list. Preferred Experience: list. Ideal Candidate Profile: description. Why choose Addison IT? includes Pay, Benefits & Bonuses, Permanent Employment, Connections, Options, Professional Development. Also Addison Group EEO etc (boilerplate to remove). We need to include sections: About the role (maybe Overview?), Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which sections have content. - About the role: we can use Overview paragraph(s) as about the role. Could also include Role, Position Type, Location maybe as metadata but we should not repeat job title as heading. We can include a short

for metadata (position type, location). The instruction: do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it. So we can include a

with Position Type: Contract, Location: Oklahoma City. - Responsibilities: we have Key Responsibilities list. - Requirements: maybe Preferred Experience? Could be considered Requirements. Or we could have Requirements (mandatory) and Qualifications (preferred). The posting doesn't explicitly separate mandatory vs preferred; but we have "Preferred Experience:" list. Could treat that as Requirements or Qualifications. We'll need to decide. - Qualifications: maybe Ideal Candidate Profile? Or we could treat Ideal Candidate Profile as Qualifications. - Skills: maybe we can extract skills from responsibilities and preferred experience (SQL, Snowflake, etc). But we should not invent content; we need to preserve substantive information. If we create a Skills section, we need to have actual content from posting. The posting includes many skill mentions: advanced SQL development, Snowflake, Oracle, ETL/ELT, dimensional modeling, dbt, Informatica, Git, etc. Those are substantive. So we can create a Skills section with a list of those. - Benefits: we have benefits line: medical, dental, vision insurance benefits, 401K. Also later "Benefits & Bonuses: You are eligible for medical, dental, vision insurance insurance benefits, 401K, and monetary bonuses". So we have benefits. - Pay: we have Pay Rate Range: Open, Based on Experience. Also later "Pay: We negotiate high salaries using U.S. Bureau of Labor Statistics". That's vague but still mentions pay. However instruction: never create Pay/Schedule/Benefits sections unless the posting actually states them. It does state Pay Rate Range: Open, Based on Experience. That's specific enough? It says open, based on experience. That's not a number but it's stating pay is open based on experience. That's still stating something about pay. So we can include Pay section with that sentence. - Schedule: not mentioned. No schedule info. So we should not include Schedule section. - About the role: we have overview paragraphs. Now we need to remove boilerplate: EEO, equal-opportunity, scam-warning, navigation, cookie, legal, duplicated lines, application instructions. Also remove "Please contact us today to discuss this opportunity!" maybe considered application instruction? It's a call to action; might be considered application instruction. Safer to remove. Also remove "Why choose Addison IT?" maybe that's promotional but could be considered boilerplate? It's not EEO but it's about the agency. Might be considered not substantive to the role. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. "Why choose Addison IT?" is not exactly those categories, but could be considered promotional fluff. However it contains details about Pay, Benefits & Bonuses, Permanent Employment, Connections, Options, Professional Development. Some of those are substantive (Pay, Benefits). But we already have Pay and Benefits sections from the posting. The "Why choose Addison IT?" section repeats benefits and pay info; we could keep the unique info (Permanent Employment, Connections, Options, Professional Development) but those are not required sections. We could incorporate them into About the role or maybe a separate section like "About the Agency" but not in allowed headings. Since we only allowed headings list, we should not create extra headings. So we could incorporate that info into a

under About the role or maybe under Benefits? But it's not benefits. Might be better to drop it as it's not required and could be considered boilerplate. The instruction says remove duplicated lines. This section may be considered duplicated of benefits/pay. So we can drop it. Thus final HTML:

About the role

Position Type: Contract

Location: Oklahoma City

[Overview paragraph(s)]

We need to preserve all substantive information from overview. Let's extract overview text: "Our client is seeking a Senior Data Engineer Consultant to support the implementation of a new enterprise data warehouse platform built on Snowflake. This individual will play a critical role in designing, developing, and supporting enterprise data pipelines that consolidate information from multiple business systems into a centralized reporting and analytics environment. The consultant will work alongside architects, business stakeholders, and technical teams to build scalable data solutions while also supporting existing production data environments during the transition. This is a long-term opportunity for an experienced data engineering professional who thrives in complex enterprise environments and enjoys solving large-scale data integration challenges." We can put that in

. Now Responsibilities: list items from Key Responsibilities. We need to output

• for each. Let's list them: - Design, develop, test, deploy, document, and support enterprise data pipelines and transformation processes. - Develop and maintain source-to-target ingestion and transformation pipelines for structured enterprise data. - Write, optimize, test, and troubleshoot complex SQL in Snowflake and Oracle environments. - Implement transformation logic, dimensional models, historical data loads, reference data management, and reconciliation controls. - Support identity matching, master data management, crosswalks, and governance-related data processes. - Partner with source system stakeholders to profile data, identify anomalies, document business rules, and resolve data quality issues. - Develop automated data quality checks, monitoring, auditing, exception handling, and operational alerting processes. - Create and execute unit, integration, regression, performance, and reconciliation testing for data pipelines. - Tune workloads and queries for performance, reliability, scalability, and cost optimization. - Utilize source control, code review, and deployment practices to support enterprise development standards. - Document data flows, transformations, dependencies, runbooks, recovery procedures, and support processes. - Troubleshoot and resolve production data issues across data warehouse and operational reporting environments. - Transfer knowledge to internal teams and assist with establishing sustainable data engineering standards and best practices. Now Requirements: we could use Preferred Experience list as Requirements. But we also have Ideal Candidate Profile which could be Qualifications. Let's decide: Requirements (mandatory) maybe not explicitly given; but we can treat Preferred Experience as Requirements (since they are preferred but still substantive). Qualifications could be Ideal Candidate Profile. Alternatively we could have Requirements = Preferred Experience, Qualifications = Ideal Candidate Profile, Skills = extracted skills list. Let's extract Preferred Experience items: - Demonstrated experience performing hands-on data engineering in complex enterprise environments. - Advanced SQL development, optimization, and performance tuning expertise. - Strong production experience with Snowflake, including data loading, transformation, security, workload optimization, and operational support. - Experience building and supporting ETL, ELT, data integration, and orchestration pipelines. - Strong understanding of dimensional modeling, normalized database structures, historical data management, slowly changing dimensions, and source-to-target mapping. - Experience implementing automated testing, monitoring, reconciliation, and data quality controls. - Experience utilizing Git-based source control and structured software development practices. - Experience supporting Oracle databases, operational data stores, or enterprise data warehouse environments. - Experience with dbt, Informatica, or comparable enterprise data integration platforms is highly preferred. - Experience integrating enterprise systems such as ERP, HCM, CRM, admissions, learning management, or comparable business applications. - Snowflake certifications or related data engineering certifications are a plus. Now Ideal Candidate Profile paragraph: "Senior-level data engineering professional capable of working independently in complex environments. Strong problem solver with exceptional SQL and data modeling expertise. Comfortable balancing new platform implementation efforts while supporting existing production workloads. Detail-oriented with a strong focus on data quality, governance, reliability, and operational excellence. Collaborative team player who can effectively work with architects, business stakeholders, and technical teams. Excellent communicator capable of translating technical concepts into business value. Passionate about establishing scalable processes, reusable frameworks, and long-term engineering standards. Experience supporting large enterprise data initiatives, analytics platforms, or institutional reporting environments is highly desirable." We can put that as Qualifications. Now Skills: we can extract skill keywords from responsibilities and preferred experience: SQL (advanced, optimization, performance tuning), Snowflake, Oracle, ETL/ELT, data integration, orchestration, dimensional modeling, normalized database structures, historical data management, slowly changing dimensions, source-to-target mapping, automated testing, monitoring, reconciliation, data quality controls, Git-based source control, dbt, Informatica, ERP, HCM, CRM, admissions, learning management, Snowflake certifications, etc. But we must not invent; we can list them as they appear in the text. Better to create a list of distinct skills mentioned. Let's pull from the text: - Advanced SQL development - SQL optimization - Performance tuning - Snowflake (data loading, transformation, security, workload optimization, operational support) - Oracle databases - ETL, ELT - Data integration - Orchestration pipelines - Dimensional modeling - Normalized database structures - Historical data management - Slowly changing dimensions - Source-to-target mapping - Automated testing - Monitoring - Reconciliation - Data quality controls - Git-based source control - Structured software development practices - dbt - Informatica - Enterprise data integration platforms - ERP systems - HCM systems - CRM systems - Admissions systems - Learning management systems - Snowflake certifications - Data engineering certifications We can create a
  • list. Now Benefits: we have "You are eligible for medical, dental, vision insurance benefits, 401K". Also later "Benefits & Bonuses: You are eligible for medical, dental, vision insurance benefits, 401K, and monetary bonuses". We'll combine: medical, dental, vision insurance, 401K, monetary bonuses. Pay: we have "Pay Rate Range: Open, Based on Experience". Also "Pay: We negotiate high salaries using U.S. Bureau of Labor Statistics". We'll include both sentences maybe. Now schedule: none, omit. Now we need to ensure we don't repeat job title as heading. We are not. We need to output only HTML fragment. Let's craft:

    About the role

    Position Type: Contract

    Location: Oklahoma City

    Our client is seeking a Senior Data Engineer Consultant to support the implementation of a new enterprise data warehouse platform built on Snowflake. This individual will play a critical role in designing, developing, and supporting enterprise data pipelines that consolidate information from multiple business systems into a centralized reporting and analytics environment. The consultant will work alongside architects, business stakeholders, and technical teams to build scalable data solutions while also supporting existing production data environments during the transition. This is a long-term opportunity for an experienced data engineering professional who thrives in complex enterprise environments and enjoys solving large-scale data integration challenges.

    Responsibilities