Defines and evolves the data engineering vision by setting modern, cloud‑native standards that ensure scalable platforms and reusable tooling, enabling teams to build solutions faster and with greater consistency.
Leads, mentors, and grows the data engineering team by developing technical capability and operational rigor, raising engineering quality so the organization delivers more reliable and impactful data outcomes.
Builds and maintains core data platforms and primitives in ways that remove friction for machine learning, analytics, and finance partners, ensuring they can access trustworthy, production‑ready data when they need it.
Establishes reusable patterns, tooling, and observability frameworks that empower practitioners to independently build, operate, and extend robust data and ML pipelines, reducing dependency bottlenecks.
Partners with machine learning, analytics, finance, and peer data engineering groups to align architectures and standards, ensuring cohesive roadmaps and clear ownership that accelerate enterprise‑wide data progress.
Drives well‑governed, production‑ready data products by balancing flexibility with reliability, enabling measurable business and model impact through high‑quality, scalable data assets.

Bachelor's Degree or equivalent experience in Computer Science, Data Engineering, Data Science, Software Engineering, or a related technical field required
Master's Degree preferred
5+ years leading data engineering efforts in complex, cross-functional environments supporting ML and analytics workloads required
Direct people leadership experience required.
Proven ability to lead and stay hands-on building and operating cloud-native data platforms: Airflow (or similar) orchestration, Kafka streaming, and RDBMS foundations (e.g., PostgreSQL).
Experience with lakehouse/warehouse solutions (e.g., Databricks/Delta, Snowflake) and production-grade platform practices (CI/CD, monitoring, security).
Demonstrated ability to set technical direction and influence architecture beyond your immediate team.
Proven commitment to mentoring, upskilling, and building high-leverage engineering teams.
Pragmatic mindset: able to balance opinionated defaults with flexibility and build tools that teams want to adopt rather than are forced to use.

Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 6 company holidays per year.
6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required.
Employee discounts, tuition reimbursement, student loan refinancing and free access to financial counseling, education, and tools.
Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.

Manager, Data Engineering

Key skills