Senior Data Engineer

Role overview Own the data pipelines, warehouse models, and access controls that support growth, customer lifecycle operations, and brokerage reporting. The work focuses on keeping information accurate and timely as it moves between business systems, the warehouse, and external platforms, including in a regulated financial setting. You will work across a broad surface area with a small team and partner closely with Marketing, Product, Operations, and engineering.

Responsibilities - Ingest and reconcile marketing, product, customer lifecycle, and brokerage data, and send verified outcomes back to external platforms. - Resolve customer identities across the journey from anonymous visit through account opening, verification, funding, and first trade. - Build and maintain layered warehouse models, with defined data grain, tests, and suitable incremental processing. - Set data contracts with upstream teams and platform owners to catch schema changes and missing fields early. - Monitor completeness, freshness, volume, and outbound syncs; investigate discrepancies and prevent recurring incidents. - Apply role-based access, personal-data masking, retention rules, and auditability; choose batch, change-data-capture, or streaming approaches based on consumer needs.

Requirements - At least five years in data or analytics engineering, including responsibility for production pipelines. - Strong SQL and Python skills and production experience with dbt models, tests, and incremental builds. - Practical experience integrating third-party and application data, handling schema changes, duplicates, resynchronization, and late or missing records. - Experience sending warehouse data to downstream tools or platforms and verifying it after delivery. - Hands-on data quality and governance experience, including reconciliation, monitoring, access controls, masking, retention, and audit trails. - Familiarity with financial or brokerage data such as account opening, identity checks, funding, transfers, trading, and settlement; able to work independently amid unclear requirements.

Nice to have - Identity resolution across web, app, and account records; marketing attribution and conversion feeds; or lifecycle and CRM integrations. - Experience with BI or AI semantic layers, workflow orchestration, Kubernetes, regulated retention and audit needs, or an early-stage data team.

Benefits and work setup - Base salary range: $150,000–$250,000. - Equity, 401(k) matching, gender-neutral parental leave, and medical, dental, and vision coverage. The listing also describes in-office amenities.