Director, Data Engineering

Axial Search is a specialist executive search firm focused on placing leaders who help organizations navigate AI transformation.

About the Market

We've tracked 200+ senior-level data engineering postings across the US in the last six months, with the strongest concentration in California, Texas, and New York. Hiring spans IT services, professional services, financial services, healthcare, and manufacturing—sectors racing to scale data infrastructure for AI workloads. Compensation for this cohort ranges from $220K to $440K annually. The strongest candidates bring 8+ years of hands-on data engineering experience, have shipped large-scale data platforms end-to-end, and can articulate both the technical architecture and the business outcomes it enables.

Responsibilities

• Own the design, build, and optimization of data pipelines and infrastructure that power analytics, AI, and machine learning initiatives across the organization
• Lead a team of data engineers and analytics engineers; set technical direction, mentor individual contributor growth, and drive execution on roadmap priorities
• Partner with data science, ML engineering, and analytics teams to understand data requirements and translate them into scalable platform solutions
• Drive decisions on data stack architecture—storage, compute, orchestration, data quality—and shepherd migrations or modernizations when needed
• Establish data governance, quality standards, and documentation practices that scale with organizational growth
• Own performance and cost optimization for data infrastructure; track and report on pipeline SLOs and system health
• Collaborate with product, engineering, and business teams to prioritize data platform features and resolve blockers in real time

Requirements

• 8+ years of data engineering experience, with at least 3 years in a senior individual contributor or team lead role shipping production data systems
• Deep fluency with modern data stack tools: cloud data warehouses (Snowflake, BigQuery, Redshift), orchestration (Airflow, dbt, Prefect), and streaming or batch pipeline frameworks
• Proven ability to design and scale data platforms from architecture through implementation; experience optimizing for cost, latency, and reliability
• Strong leadership presence: you've hired, mentored, and developed engineers; you set technical standards and drive consensus on architectural decisions
• Track record of partnering cross-functionally with data science, ML, analytics, and product teams to deliver business outcomes through data infrastructure
• Comfort with ambiguity and ownership mindset; you ship incrementally, measure impact, and iterate based on what you learn

Pay

$220K–$440K annually