Senior Data Engineer

Senior Data Engineer at Amazon Development Center U.S., Inc. onsite in Seattle, WA, with a yearly salary range of USD 154,600 - 209,100.

Responsibilities

• Identify limitations and opportunities in data processing tools, drive improvements and innovation, define data processing guidelines, and ensure best practices across pipelines. Examples include redesigning ingestion frameworks for new AWS service telemetry data or creating reusable transformation patterns adopted by multiple teams.
• Define and own data architecture at the team level, aligning solutions with business problems, data challenges, security, scalability, and cost efficiency; make informed trade-offs between short-term tech needs and long-term business goals.
• Produce exemplary code that is secure, maintainable, scalable, extensible, and easy for others to contribute to; simplify and optimize data solutions while removing bottlenecks.
• Define and own infrastructure architecture at the team level; anticipate data management and access patterns, evolve the tech stack to remove bottlenecks, and deliver secure, scalable, long-lasting systems; establish team guidelines for infrastructure management and automation.
• Solve complex, ambiguous problems, such as designing cross-domain data models that unify billing, usage, and service telemetry data, or combining multiple datasets to unlock previously unsolvable insights; identify areas prone to data misinterpretation or gaps in data contracts.
• Break work into parallel tasks and coordinate self-contained delivery, driving projects to completion with dependencies on peers or other teams.
• Influence related teams' data architecture and software design; mentor and develop others; provide technical assessments for promotions; build consensus across discordant viewpoints.
• Drive data engineering best practices including Data Discovery, Naming Conventions, Operational Excellence, and Data Security; ensure data is auditable, available, and accessible.
• Proactively fix data architecture deficiencies and propose larger cross-team projects; advance improvements via code reviews, design discussions, planning, and operational reviews.
• Participate in on-call rotation and own the operational health of data systems; establish monitoring, alarming, runbooks, and SLA tracking; pursue continuous reliability and incident response improvements.

Requirements

• 7+ years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language such as Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices
• Experience with MPP databases such as Amazon Redshift
• Experience building and operating highly available, distributed systems for data extraction, ingestion, and processing of large data sets

Technologies

• AWS EMR
• AWS Glue
• Amazon Redshift
• AWS Lambda
• Large Language Models (LLMs)
• Hadoop
• Hive
• Spark
• Python
• Java
• Scala
• NodeJS
• SQL

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription)
• Basic Life & AD&D insurance and option for Supplemental life plans
• Employee Assistance Program (EAP)
• Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave