Head of Data Engineering
- Lead Data Engineering function build-out from zero: own all pipelines and establish freshness monitoring across Azure (Data Factory, ADLS, Databricks) and Google Cloud (BigQuery, Looker), plus third-party integrations (Plaid, FactorTrust, Zendesk, AirCall, Amplitude, Epic)
- Implement medallion architecture: bronze (raw ingestion) → silver (curated per consumer domain) → gold (feature stores + agent-ready data planes for ML models and AI workflows)
- Build data catalog and dictionary with canonical join keys and full applicant data map; define schema governance and data contracts with upstream systems
- Deliver a diagnostic and roadmap within the first 30 days: architecture inventory, business unit needs assessment, sequenced build plan, and resource requirements presented to executive stakeholders
- Stand up intake and request-management process for cross-functional stakeholders: Underwriting, Collections, Marketing, Product, Data Science, Executive
- Implement audit trails, identity governance, and cost monitoring across BigQuery and Azure; establish cross-functional contracts with Engineering and Product so application changes ship with observability intact
- Evaluate and drive cloud consolidation strategy: current state is Azure + GCP (BigQuery/Looker); strategic direction is Azure + Databricks — propose, justify, and execute the path
- Hire and lead the data engineering team as the function scales to +1 platform engineer + 1 analyst-engineer within months 3–9
- Senior Data Engineer with 5+ years designing and operating production data pipelines at scale, ideally at a fintech or lending company where data became the gating constraint on growth
- C1 English level or higher — role requires clear communication with a US-based executive team and non-technical stakeholders
- Demonstrated ability to produce a diagnostic and roadmap within the first weeks in a new role and present it credibly to technical and non-technical audiences
- Experience implementing medallion architecture with explicit schema contracts and lineage between layers
- Strong proficiency in Azure (Data Factory, ADLS) and Google Cloud (BigQuery); Databricks experience (asset bundles, Unity Catalog, GitHub Actions deployment) is a strong plus
- Track record of hiring and leading data engineering teams (2–5 engineers), including standing up intake processes and cross-functional data contracts
- Production-level Python and strong SQL fluency including BigQuery-specific optimization patterns (partitioning, clustering, cost-control idioms)
- Hands-on experience with orchestration frameworks: Airflow, Dagster, or Azure Data Factory pipelines
- Comfortable operating hands-on alongside the team — this is not a purely managerial role
We offer a 100% remote work model with global flexibility, supporting continuous career development through training and leadership opportunities. Niuro provides robust administrative support, enabling you to focus on impactful work and project delivery. Successful contractors may transition to long-term, full-time roles to support ongoing collaboration with our U.S. clients. We emphasize technical excellence, collaboration, and a growth-oriented learning culture within a global team.