Senior Data Engineer (AWS)

Quick Facts

• Role: Senior Data Engineer (AWS)

• Focus: Governed data platform and agentic data infrastructure for enterprise AI/analytics

Description

You will architect and build the governed foundations that determine whether every AI agent answer is trustworthy, including a multi-tier governed data warehouse, canonical datasets, an MCP interface over production data systems, and a graph-based knowledge layer. You’ll define platform standards and translate complex constraints into roadmap decisions, while collaborating with BI engineers, data engineers, and data scientists. The role emphasizes system thinking, deep technical ownership, and production-grade operations.

Responsibilities

• Data platform architecture and governance, including warehouse topology, workload isolation, access control design, and production migration sequencing

• Define and enforce architectural standards, data contracts, and quality gates for source-to-analytics/AI flows

• Design and build canonical datasets across core business domains with governed relationships and metadata standards

• Build secure, privacy-compliant, efficient data pipelines for analytics, ML, and agent consumption

• Own monitoring, alarming, runbooks, and SLA tracking; participate in on-call rotation and conduct operational health reviews

• Build and maintain an MCP layer enabling LLMs/agents to retrieve accurate, role-appropriate business context

• Create and evolve a graph-based knowledge layer (Amazon Neptune Analytics or equivalent) for semantic traversal across business objects

• Provide technical leadership and mentorship: best practices, naming conventions, access security, documentation, and design reviews

Requirements

• 5+ years of data engineering experience

• Experience with at least one modern programming/scripting language: Python, Java, Scala, or NodeJS

• Experience with MPP databases such as Amazon Redshift

• Experience providing technical leadership and mentoring engineers

• Experience with data warehouse architectures, data modeling, ETL/ELT, reporting/analytic tools, data structures, and hands-on SQL

Benefits

• Comprehensive benefits including health insurance (medical, dental, vision, prescription), Basic Life & AD&D, Supplemental life options, EAP, mental health support, medical advice line, flexible spending accounts

• 401(k) matching, paid time off, and parental leave

• Sign-on payments and restricted stock units (RSUs)