Lead Data Engineer

This role has meaningful ownership across Dave’s data platform. You’ll work across business domains and platform capabilities, solving complex data challenges while helping establish the technical patterns that make our systems easier to build, operate, and scale.

You’ll partner closely with engineering and business teams to turn evolving needs into durable solutions. Not everything will be fully defined—you’ll help clarify the path, make thoughtful architecture trade-offs, and ensure we’re building systems that hold up over time.

• Lead the design, implementation, operation, and evolution of production data pipelines and core platform capabilities.
• Build and improve integrations across APIs, files, CDC and event sources, cloud services, and internal systems.
• Establish strong patterns for data modeling, orchestration, testing, data quality, observability, retries, backfills, and recovery.
• Improve Snowflake, dbt, and Airflow/Cloud Composer workloads with a focus on reliability, scalability, performance, and cost.
• Lead technical design reviews, clarify system boundaries, and help teams make thoughtful architecture and delivery trade-offs.
• Strengthen the broader engineering organization through mentorship, documentation, standards, and durable solutions that reduce operational burden and single-person dependencies.

The systems you build will help teams across Dave access reliable data and make better decisions. By improving the reliability and scalability of our data platform, you’ll help create a stronger foundation for our products, operations, and continued growth.

• 5+ years of software or data engineering experience, including significant ownership of production data systems.
• Strong Python and SQL skills, along with solid software engineering fundamentals including testing, code review, version control, and CI/CD.
• Experience with a modern cloud data warehouse such as Snowflake, Big Query, or Redshift.
• Experience with orchestration and transformation frameworks such as Airflow/Cloud Composer and dbt, or comparable technologies.
• Strong understanding of data modeling, incremental processing, data quality, observability, and production recovery.
• Demonstrated architecture judgment and experience providing technical leadership and mentorship across teams.
• Ability to navigate ambiguity, clarify ownership, and communicate technical and business trade-offs clearly.

• Fintech or other high-stakes or regulated data experience.
• CDC, streaming, event-driven, or high-volume integration experience.
• Experience with GCP technologies such as Dataflow, Pub/Sub, and Cloud Storage.
• Experience with metadata, lineage, semantic layers, governance, privacy, or AI-ready data platforms.

You take responsibility for outcomes, not just deliverables. You’re comfortable going deep enough to diagnose a production issue while also stepping back to understand how a technical decision affects reliability, cost, partner teams, and the broader business. You care about building systems that hold up over time and know when to optimize for speed versus durability.

You also make the people around you more effective. You share context, invite feedback, mentor other engineers, and create standards and documentation that reduce dependency on any one person. When priorities or information change, you adjust thoughtfully without losing sight of the outcome.

You’ll have meaningful autonomy and the opportunity to shape both systems and engineering practices. We make decisions using data, technical judgment, and input from the teams affected by them. Priorities will evolve as Dave grows, and you’ll have a voice in…