Head of Data Engineering

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 growthC1 English level or higher — role requires clear communication with a US-based executive team and non-technical stakeholdersDemonstrated ability to produce a diagnostic and roadmap within the first weeks in a new role and present it credibly to technical and non-technical audiencesExperience implementing medallion architecture with explicit schema contracts and lineage between layersStrong proficiency in Azure (Data Factory, ADLS) and Google Cloud (BigQuery); Databricks experience (asset bundles, Unity Catalog, GitHub Actions deployment) is a strong plusTrack record of hiring and leading data engineering teams (2–5 engineers), including standing up intake processes and cross-functional data contractsProduction-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 pipelinesComfortable operating hands-on alongside the team — this is not a purely managerial role 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 systemsDeliver a diagnostic and roadmap within the first 30 days: architecture inventory, business unit needs assessment, sequenced build plan, and resource requirements presented to executive stakeholdersStand up intake and request-management process for cross-functional stakeholders: Underwriting, Collections, Marketing, Product, Data Science, ExecutiveImplement 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 intactEvaluate and drive cloud consolidation strategy: current state is Azure + GCP (BigQuery/Looker); strategic direction is Azure + Databricks — propose, justify, and execute the pathHire and lead the data engineering team as the function scales to +1 platform engineer + 1 analyst-engineer within months 3–9 Niuro connects projects with elite tech teams to empower partnerships with top-tier U.S. companies. Our mission is to simplify global talent acquisition through innovative solutions, enabling continuous growth and delivery excellence. You will be the first Head of Data Engineering at a US-based fintech processing ~1,000 merchant cash advances monthly. Build the data function from zero: own all pipelines, implement medallion architecture (bronze/silver/gold), and establish governance, monitoring, and cost controls across Azure and BigQuery. This is a peer role to the Head of Engineering and Chief Data Scientist, reporting to the CEO, with a clear path to lead a small team from month three onward You’ll join a global, remote-first environment that supports ongoing training, leadership development, and a culture of technical excellence. This role focuses on building scalable integrations that underpin complex workflows and data pipelines for our clients. 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. Prior experience at a fintech operating Plaid integrations or equivalent open banking / bank-data aggregation productsExperience migrating reporting layers from GCP (BigQuery/Looker) to Azure-native tooling (Power BI, Microsoft Fabric) — Fundo is actively evaluating this consolidationHands-on with Databricks Asset Bundles and GitHub Actions for automated pipeline deployment; experience with Unity Catalog and DLT is a plusExperience deploying agentic or AI-assisted data workflows — semantic layers, LLM-accessible gold-layer data planes, or AI-assisted pipeline monitoring (Slack-integrated alert agents, auto-PR generation)Background working with gig economy, MCA, or informal-worker financial data — familiarity with transaction-heavy, non-bureau underwriting data shapes is a meaningful acceleratorSpanish — most of the engineering team operates bilingually