Director, Data Engineering

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What the market looks like

We've tracked 500+ senior-level data engineering postings in the US over the last six months, with hiring concentrated in California, Texas, and New York across technology, financial services, healthcare, and professional services. Director-level data engineering roles typically offer $190K–$240K base salary, with total compensation ranging to $440K at the 95th percentile when equity and performance bonuses are factored in. The strongest candidates bring 8+ years of hands-on engineering experience, a track record of building and scaling data platforms from the ground up, and the ability to balance deep technical leadership with cross-functional stakeholder management. They're comfortable working across the full data stack—from infrastructure and pipeline design through analytics and ML operationalization—and they lead by mentoring engineers and setting architectural standards rather than hands-on coding alone.

Job responsibilities

• Own the design, build, and evolution of enterprise-scale data platforms and pipelines, including decisions around architecture, tooling, and infrastructure that serve downstream analytics, ML, and business intelligence teams

• Lead a team of data engineers, establishing engineering practices, code standards, and a culture of reliability and iteration; mentor engineers through hands-on technical guidance and career development

• Partner with data science, ML, and analytics leaders to understand data requirements and translate them into scalable, production-grade solutions

• Drive data quality, governance, and observability initiatives across the organization, ensuring pipelines are reliable, documented, and auditable

• Evaluate and integrate new tools, technologies, and frameworks—cloud platforms, distributed compute systems, real-time streaming, modern data warehouses—into the existing stack

• Collaborate with infrastructure and platform teams on cost optimization, security, and operational efficiency of data systems

• Own roadmap prioritization and execution, balancing technical debt, team capacity, and business priorities

Candidate requirements

• 8+ years of data engineering experience, with at least 2–3 years in a leadership or senior IC role building and owning data platforms at scale

• Demonstrated proficiency across the data stack: SQL, distributed systems, ETL/ELT frameworks (Apache Spark, Airflow, or equivalent), and cloud data platforms (Snowflake, BigQuery, Redshift, or similar)

• Track record of designing and shipping systems that handle high-volume, production data; comfort with data modeling, schema design, and performance optimization

• Leadership experience mentoring engineers, conducting technical reviews, and setting architectural direction for teams

• Strong communication skills; ability to translate technical decisions into business impact and partner across product, analytics, and ML functions