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# Sr. Data & Analytics Engineer, Amazon Leo

- **Company:** Amazon.com, Inc.
- **Location:** Redmond, WA, United States
- **Experience:** Expert
- **Salary:** $168,100.0 - $227,400.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Business Analytics Applications, Data Analysis, Automation of Tests, Big Data, Computer Programming, Databases, Computer Engineering, Data Validation, Data Integration, Extract Transform Load (ETL), Data Systems, Database Applications, Database Queries, Software Design Patterns, Hardware Design, Monitoring of Systems, Python (Programming Language), Meta-Data Management, Software Engineering, Statistical Process Control (SPC), Data Streaming, Test Data, Management of Software Versions, Data Ingestion, Data Strategy, Information Technology, Data Lineage, Data Analytics, Build Process, Data Management, Data Pipelines, Engineering Base, Programming Languages
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1e6725239e973915

## About the Role

* 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., * 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.

## Description

* 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.