Sr. Data & Analytics Engineer, Amazon Leo

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info. Remove boilerplate like EEO, accommodations, etc. Also remove application instructions. Must not include placeholder sections like Pay/Schedule/Benefits unless posting actually states them. The posting includes salary range: "USA, WA, Redmond - 168,100.00 - 227,400.00 USD annually". Also mentions benefits: "Amazon also offers comprehensive benefits including health insurance ... 401(k) matching, paid time off, and parental leave." Also mentions sign-on payments and RSUs. So we have Pay and Benefits sections. Schedule not mentioned, so omit. We need sections: About the role (description), Responsibilities (key job responsibilities), Requirements (basic qualifications?), Qualifications (preferred qualifications?), Skills (maybe combine basic/preferred? But we need to follow instruction: use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide what goes where. We have description paragraph about Amazon Leo and Battery org. That's About the role. Responsibilities: list of responsibilities bullet points. Requirements: basic qualifications? Could be "Basic Qualifications". We'll put under Requirements. Qualifications: "Preferred Qualifications". We'll put under Qualifications. Skills: maybe combine programming languages etc? But we could also put under Skills the specific technical skills: Python, SQL, ETL, etc. However the posting already includes those in qualifications. Might be redundant. But we need to follow instruction: prefer a few substantive sections over many thin ones. Could combine Requirements and Qualifications into one? But headings are prescribed; we can omit sections if no content. We could put Requirements = Basic Qualifications, Qualifications = Preferred Qualifications, Skills = maybe not needed if covered. But we could still include Skills with specific technical skills extracted: Python, SQL, ETL/ELT, data pipelines, APIs, etc. However that would duplicate content. The instruction says preserve ALL substantive information; do NOT invent or summarize away detail. Duplication is okay as long as we preserve info. But we should avoid unnecessary duplication? Not prohibited. However better to keep sections distinct: Requirements = Basic Qualifications (including years experience, degree). Qualifications = Preferred Qualifications (including advanced degree, hardware experience, etc). Skills = maybe list of specific technical skills: Python, SQL, ETL/ELT, data validation, schema design, AWS, etc. But those are already in basic qualifications. Could still list them. Pay: include salary range and mention sign-on payments and RSUs. Benefits: list benefits. We must not include boilerplate like EEO, accommodations, etc. Also remove duplicated lines. Let's extract content. About the role: first paragraph: "Amazon Leo is Amazon's low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. The Amazon LEO Battery organization develops and validates advanced battery systems that power Amazon’s Low Earth Orbit satellite constellation. Our team works across battery engineering, test and validation, manufacturing, automation, systems engineering, quality, reliability, software, and production operations. As a Senior Data & Analytics Engineer, you will own the data infrastructure, analytics, and engineering tools that connect battery development, test, manufacturing, and production data. You will enable end-to-end traceability, automate data processing and reporting, and develop scalable tools that help engineers understand product performance, identify failures and trends, improve processes, and make faster technical decisions." That's About the role. Responsibilities: list bullet points from "Key job responsibilities". Let's capture each: - Architect and maintain scalable data pipelines and platforms for battery test, manufacturing, laboratory, and production systems. - Build unified data models connecting cells, PCBAs, battery packs, test results, manufacturing processes, equipment, configurations, and quality records. - Establish end-to-end product and test traceability across serial numbers, cell lots, hardware and software revisions, test procedures, equipment, calibration status, and nonconformance data. - Develop automated data ingestion, transformation, validation, and processing from test systems, manufacturing equipment, databases, APIs, and engineering files. - Build engineering analytics, dashboards, and tools for test performance, lifecycle data, FPY, SPC, production trends, equipment performance, and failure investigations. - Develop automated data-analysis and reporting workflows that convert raw test data into engineering metrics, pass/fail results, trends, and actionable insights. - Establish data quality, lineage, metadata, and schema standards to ensure engineering data is accurate, reproducible, and trustworthy. - Develop reusable APIs, libraries, datasets, and applications that allow engineering teams to efficiently access and analyze battery data. - Partner with Battery Test, Systems, Manufacturing Automation, ATE Software, Quality, Reliability, Manufacturing, and Production teams to translate engineering needs into scalable data and analytics solutions. - Drive technical architecture, analytics standards, tool development, documentation, and long-term battery data strategy. Also Export Control Requirement: "Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum." This is a requirement; could be placed under Requirements. Requirements (Basic Qualifications): list: - 5+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team - Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or majors relating to these fields - Experience developing scalable data pipelines, databases, data models, APIs, or engineering data platforms. - Strong programming experience with Python or another modern programming language and strong SQL skills. - Experience developing data-analysis, visualization, or engineering applications using large or complex datasets. - Experience with ETL/ELT pipelines, data validation, schema design, and integration of multiple data sources. - Experience translating engineering or customer requirements into scalable software, data, or analytics solutions. - Export Control Requirement: U.S. citizen/national, permanent resident, refugee/asylee. Qualifications (Preferred Qualifications): list: - Bachelor's degree in computer science or equivalent - Master's degree or above in computer science, engineering, mathematics or equivalent, or Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent - Experience working with hardware development, automated test, manufacturing, aerospace, automotive, semiconductor, battery, or other complex engineering environments. - Experience analyzing high-volume or time-series data from test equipment, sensors, instrumentation, or manufacturing systems. - Experience developing engineering dashboards, automated reports, statistical analysis tools, or data-driven applications. - Experience integrating data with MES, manufacturing traceability, quality management, laboratory, or equipment-monitoring systems. - Experience with AWS data technologies, APIs, streaming architectures, data lineage, metadata management, or schema versioning. Skills: Could list specific technical skills: Python, SQL, ETL/ELT, data pipelines, APIs, data modeling, AWS, etc. But to avoid duplication, maybe we can omit Skills section and put those under Requirements/Qualifications. However instruction says we can include sections only when posting has real specific content. It does have specific skills (Python, SQL, etc.) but they are already in Requirements. Could still create Skills section with those items. But that would duplicate. The instruction says preserve ALL substantive information; duplication is not prohibited but might be considered redundant. However they said "do NOT invent or summarize away detail." Duplication preserves detail, not summarizing away. It's okay but might be considered thin. Better to combine skills into Requirements and Qualifications and omit Skills section to avoid thin sections. But we need to follow the heading list; we can omit Skills if no distinct content beyond what's already covered. The posting does have explicit "Strong programming experience with Python or another modern programming language and strong SQL skills." That's a skill. Could be placed under Skills. But we already have it under Requirements. If we put it under Skills, we would need to remove from Requirements to avoid duplication, but then we lose some detail from Requirements (the years of experience etc). We could keep both but it's duplication. I'd rather keep Requirements as is (including years, degree, etc.) and put Skills as a separate list of specific technical skills (Python, SQL, ETL/ELT, APIs, AWS, etc.) but we would need to ensure we don't lose any info. The Requirements already includes those skills; moving them to Skills would still preserve them, just in a different place. That's acceptable. Thus: Requirements: list of experience years, degree, mentorship, etc. (excluding specific technical skills maybe). But we need to keep all substantive info; we can keep the years etc and also keep the technical skills under Skills. Let's decide: Requirements (Basic Qualifications) will contain: - 5+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team - Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or majors relating to these fields - Experience developing scalable data pipelines, databases, data models, APIs, or engineering data platforms. - Experience developing data-analysis, visualization, or engineering applications using large or complex datasets. - Experience with ETL/ELT pipelines, data validation, schema design, and integration of multiple data sources. - Experience translating engineering or customer requirements into scalable software, data, or analytics solutions. - Export Control Requirement: U.S. citizen/national, permanent resident, refugee/asylee. Skills will contain: - Strong programming experience with Python or another modern programming language - Strong SQL skills - Experience with AWS data technologies, APIs, streaming architectures, data lineage, metadata management, or schema versioning (maybe also under Skills) But note AWS etc is in Preferred Qualifications. Could also be under Skills. However we risk duplication. But we can keep AWS etc under Skills as well; it's okay. Qualifications (Preferred Qualifications) will contain: - Bachelor's degree in computer science or equivalent - Master's degree or above in computer science, engineering, mathematics or equivalent, or Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent - Experience working with hardware development, automated test, manufacturing, aerospace, automotive, semiconductor, battery, or other complex engineering environments. - Experience analyzing high-volume or time-series data from test equipment, sensors, instrumentation, or manufacturing systems. - Experience developing engineering dashboards, automated reports, statistical analysis tools, or data-driven applications. - Experience integrating data with MES, manufacturing traceability, quality management, laboratory, or equipment-monitoring systems. Now Benefits: list: - Sign-on payments and restricted stock units (RSUs) - Comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage) - 401(k) matching - Paid time off - Parental leave Pay: salary range: USA, WA, Redmond - 168,100.00 - 227,400.00 USD annually. We should not include location as part of Pay? Could include location in Pay section or separate. But location is not a heading; we could include location in About the role? Already there is location in salary line. We could