IT Data Platform Data Engineer

We need to output HTML fragment with sections: About the role? The posting includes Summary, Essential Duties And Responsibilities, COMPETENCIES, Qualifications, CERTIFICATES..., Work Environment And Physical Requirements, Safety Statement, ADA Statement. We must remove boilerplate like safety statement? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Safety and ADA statements might be considered legal boilerplate? Possibly they are not required to keep. The instruction says remove legal/EEO/equal-opportunity/scam-warning boilerplate. Safety statement may be considered legal? It's about safety policy; could be considered boilerplate. ADA statement also legal. Likely we should drop those. Also remove "POSTING DEADLINE This position is posted until filled." and "Job Description IT Data Platform Data Engineer Salary Grade: G05 Minimum Midpoint Maximum $94,831 - $128,022 - $161,213". Salary info: we have a Pay section? The posting includes salary range. According to rules, we should include Pay section only if posting actually states them. It does state salary range. So we should create a Pay section with that info. Also we should not repeat job title as heading. So we will not include heading for job title. We need sections: About the role? The posting has Summary (could be About the role). Responsibilities (Essential Duties And Responsibilities). Requirements (Qualifications). Skills? Could be COMPETENCIES as Skills. Benefits? Not present. Pay: we have salary range. Schedule? Not present (maybe work environment includes travel 10%). Could be Schedule? Not exactly. Work environment could be maybe a section? Not in list of allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we should map content to these headings. Use About the role for summary. Responsibilities for essential duties. Requirements maybe for qualifications? But we also have Qualifications heading allowed. Could combine? The instruction: Prefer a few substantive sections over many thin ones. So we could have About the role, Responsibilities, Requirements (including qualifications and competencies), Pay. Possibly Skills separate if we have competencies. But we could merge qualifications and competencies into Requirements? However we have both Qualifications and Skills headings allowed. Might be better to have Requirements for qualifications (education/experience) and Skills for competencies. Let's do: About the role (summary), Responsibilities (essential duties), Requirements (qualifications), Skills (competencies), Pay (salary). No Benefits, Schedule. We must not include headings with filler. Ensure we include all substantive info. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to preserve all substantive information, not invent or summarize away detail. So we need to keep details like bullet points etc. The Essential Duties list is a paragraph with many sentences separated by spaces. We need to turn into list items? The instruction: Use

  • for any list of duties/requirements/benefits. So we should split each duty into separate
  • . The duties are separated by spaces and start with capital letters? Let's parse: "Leads the design, development, and maintenance of automated data pipelines for ingesting, transforming, and storing complex structured and unstructured data from multiple evolving sources Drives collaboration with BTS and business leadership to architect reliable, scalable enterprise data solutions supporting analytics, reporting, and AI use cases Architects, builds, and oversees data integration processes, ETL/ELT workflows, and orchestration frameworks to ensure availability, performance, and resilience Establishes and enforces data quality, completeness, accuracy, and timeliness through advanced validation, proactive monitoring, and remediation processes Defines and implements sophisticated data models and structures optimized for enterprise analytics and advanced analysis Guides strategy for cloud and on-premises data platforms, including data lakes, data warehouses, and next-generation analytics environments Leads and mentors data analysts, data scientists, and junior engineers in feature engineering and model readiness Develops and governs metadata management, lineage, and documentation standards while driving adoption across the enterprise Owns compliance with data security, privacy, and regulatory requirements in alignment with enterprise policies Leads performance tuning, capacity planning, and optimization efforts for data pipelines and data storage Oversees platform health and proactively resolves complex, systemic data pipeline issues Authors and maintains advanced data engineering designs, standards, and operational procedures Exercises expert judgment in evaluating technical options, balancing cost, performance, scalability, security, and maintainability Identifies and drives innovation opportunities to modernize and expand enterprise data platforms" We can split each sentence (they are separated by spaces but each starts with a verb). We'll create
  • for each. Competencies list: similar sentences. "Expert understanding of enterprise data architecture, integration patterns, and large scale data platforms Demonstrates mastery of SQL and expert proficiency in Python, data modeling, and data integration tools Diagnoses and resolves complex data flows, system dependencies, and platform level issues Evaluates technical solutions strategically, considering long term scalability, cost, performance, and risk Champions innovation, challenges assumptions, and leads adoption of emerging technologies Leads and influences across matrixed organizations, driving consensus and alignment Facilitates enterprise coordination across data, analytics, engineering, and IT functions Defines, institutionalizes, and enforces engineering standards, best practices, and architectural guidelines Communicates persuasively with technical teams and executive audiences Interprets complex technical and business documentation and converts it into actionable engineering plans Rapidly acquires, unlearns, and instills advanced tools, frameworks, and engineering methodologies Builds trust with internal partners and cross functional teams through credibility and technical authority" We'll split each. Qualifications: "Bachelors degree in Computer Science, Information Systems, Engineering, or related field, with seven to nine years of progressively responsible experience in data engineering, data integration, or analytics platforms, or an equivalent combination of advanced education and experience. A masters degree or specialized certifications preferred" We can keep as

    or maybe list? It's not a list but we can keep as

    . Certificates: list of preferred certifications. Could be a list under Skills? But we already have Skills for competencies. Could add another section? But we prefer few sections. Could include certificates within Skills as a list? However the instruction: Use

    • for any list of duties/requirements/benefits. Certificates is a list; we could include under Skills as a sublist? But we must not invent sections. Could add a separate section? Not allowed headings besides those. Could we put under Skills as a list? Might be okay to include as
      • inside Skills section. But we need to decide. Better: Keep Skills section for competencies and also include certificates as a list within that section? Might be messy. Alternative: Create a separate section for Certifications? Not allowed heading. Could fold into Requirements as a list? But Requirements is for qualifications; we could add a list there. Given instruction to prefer few sections, we could have About the role, Responsibilities, Requirements (including qualifications and certificates), Skills (competencies), Pay. Thus Requirements section will contain both qualifications paragraph and a list of certificates. We need to use
        • for any list. So we will put certificates as a list. Now Pay section: we have salary range: "$94,831 - $128,022 - $161,213". Also Salary Grade: G05. We should include that. We must not include heading for Pay if no content? We have content. Now we need to strip boilerplate: Remove "POSTING DEADLINE This position is posted until filled." Remove "Job Description IT Data Platform Data Engineer". Also remove Safety Statement and ADA Statement. Now produce HTML. Structure:

          About the role

          Under limited direction, leads the design, build, and maintenance of enterprise-scale data pipelines and data platforms that enable advanced analytics, reporting, and AI initiatives. Partners with business and IT leadership to shape strategic data requirements, ensure robust data integration, and deliver timely access to high-quality data across the organization. Champions data engineering best practices, drives governance and security compliance, and leads continuous improvement of enterprise data infrastructure.

          Responsibilities

          • Leads the design, development, and maintenance of automated data pipelines for ingesting, transforming, and storing complex structured and unstructured data from multiple evolving sources
          • Drives collaboration with BTS and business leadership to architect reliable, scalable enterprise data solutions supporting analytics, reporting, and AI use cases
          • Architects, builds, and oversees data integration processes, ETL/ELT workflows, and orchestration frameworks to ensure availability, performance, and resilience
          • Establishes and enforces data quality, completeness, accuracy, and timeliness through advanced validation, proactive monitoring, and remediation processes
          • Defines and implements sophisticated data models and structures optimized for enterprise analytics and advanced analysis
          • Guides strategy for cloud and on-premises data platforms, including data lakes, data warehouses, and next-generation analytics environments
          • Leads and mentors data analysts, data scientists, and junior engineers in feature engineering and model readiness
          • Develops and governs metadata management, lineage, and documentation standards while driving adoption across the enterprise
          • Owns compliance with data security, privacy, and regulatory requirements in alignment with enterprise policies
          • Leads performance tuning, capacity planning, and optimization efforts for data pipelines and data storage
          • Oversees platform health and proactively resolves complex, systemic data pipeline issues
          • Authors and maintains advanced data engineering designs, standards, and operational procedures
          • Exercises expert judgment in evaluating technical options, balancing cost, performance, scalability, security, and maintainability
          • Identifies and drives innovation opportunities to modernize and expand enterprise data platforms

          Requirements

          Bachelors degree in Computer Science, Information Systems, Engineering, or related field, with seven to nine years of progressively responsible experience in data engineering, data integration, or analytics platforms, or an equivalent combination of advanced education and experience. A masters degree or specialized certifications preferred.

          • Microsoft Certified: Power BI Data Analyst Associate
          • Tableau Desktop Certified Associate
          • IBM Data Analyst Professional Certificate
          • SAS Certified Advanced Analytics Professional (Using SAS 9)
          • Data Science Council of America (DASCA)
          • Databricks Certified Data Analyst Associate
          • Google, AWS, Microsoft Azure Data Analytics certifications

          Skills

          • Expert understanding of enterprise data architecture, integration patterns, and large scale data platforms
          • Demonstrates mastery of SQL and expert proficiency in Python, data modeling, and data integration tools
          • Diagnoses and resolves complex data flows, system dependencies, and platform level issues
          • Evaluates technical solutions strategically, considering long term scalability, cost, performance, and risk
          • Champions innovation, challenges assumptions, and leads adoption of emerging technologies
          • Leads and influences across matrixed organizations, driving consensus and alignment
          • Facilitates enterprise coordination across data, analytics, engineering, and IT functions
          • Defines, institutionalizes, and enforces engineering standards, best practices, and architectural guidelines
          • Communicates persuasively with technical teams and executive audiences
          • Interprets complex technical and business documentation and converts it into actionable engineering plans
          • Rapidly acquires, unlearns, and instills advanced tools, frameworks, and engineering methodologies
          • Builds trust with internal partners and