Senior Data Engineer (Dallas)

Lead Data Engineer (AWS) — Hybrid in Dallas TX or Houston TX Location:

Hybrid (2–3 days onsite) Compensation:

$130K–$170K + Bonus + Equity Work Authorization:

No sponsorship available Relocation:

Potential light relocation support

About the Role We’re supporting a major cloud modernization initiative and building a U.S.-based data engineering capability from the ground up. As a Lead Data Engineer (AWS), you’ll play a key role in designing and delivering modern data pipelines, mentoring a team of engineers, and helping establish technical standards for a modern AWS-native data platform.

This role is a blend of hands-on engineering (60%) and technical leadership/mentorship (40%)—ideal for someone who enjoys owning complex build work while guiding others.

What You’ll Do Technical Leadership (no formal people management) Set engineering best practices, patterns, and coding standards Mentor and guide a team of ETL/data engineers Improve pipeline quality, velocity, and reliability Translate functional requirements into technical solutions Collaborate closely with product/data stakeholders Hands-On Engineering Build AWS-native data pipelines and ingestion frameworks Implement lakehouse architecture using modern open table formats Work heavily with AWS Glue, EMR, S3, Athena, Lambda, and related services Develop scalable data solutions in Python and PySpark Enable analytics, BI, and future GenAI use cases Own data pipelines end-to-end, from ingestion to production

Ideal Candidate Profile Must-Have Experience Strong, recent hands-on AWS experience (non-negotiable) Expertise with Apache Iceberg, Delta Lake, or Hudi Ability to explain data storage internals (snapshots, schema evolution, metadata layers, performance tuning) Strong Python and PySpark Proven lakehouse architecture experience Passion for hands-on engineering and building production pipelines Typically 6–10+ years of experience (open to strong 5+ years with deep AWS experience)