Founding Data Engineer

Role Overview As a Data Engineer (Platform & Customer Onboarding) at BlueAlpha, you'll own the data plumbing that makes everything else possible. Half of your time you'll be focused on customer integrations: taking marketing, product, and revenue data from our clients, ingesting and transforming it into something our models and Ul can rely on, and making sure onboarding is fast and repeatable. The other half you'll be focused on BlueAlpha's own data platform: designing schemas, building and hardening pipelines, and making clean, well-modeled data available to product, modeling, and go-to-market teams. You should enjoy both sides: talking through a CSV spec with a customer one day, then refactoring a core ELT job or warehouse schema the next. Responsibilities Own the data onboarding flow for new customers Map their data sources, define requirements, build ingestion pipelines, validate inputs, and get them to a clean go-live. Build and maintain internal data pipelines Create and improve ETL/ELT jobs that power modeling, product features, analytics, and reporting across the company. Design and evolve our data architecture Work on warehouses, schemas, table design, and transformations so that our data model is coherent, efficient, and easy to use. Validate and monitor data quality Implement schema checks, QA rules, anomaly detection, and monitoring for both customer and internal data flows. Integrate external APIs and data sources Connect marketing platforms, attribution tools, app event streams, and evenue systems into stable, reusable pipelines. Debug and resolve data issues quickly Investigate discrepancies, fix broken jobs, and communicate clearly with internal teams and customers about what's happening and why. Build internal tooling and documentation Create small utilities, runbooks, and checklists that make onboarding and ongoing operations faster and less error-prone. Continuously improve reliability and performance Reduce manual work, improve observability, and optimize pipeline cost, robustness, and latency where it matters. Qualifications Required 3+ years in data engineering, analytics engineering, or technical implementation for a data-heavy product or platform. Strong SQL (complex joins, window functions, profiling and debugging large datasets). Solid Python for data manipulation, scripting, API integrations, and simple services. Hands-on experience building and maintaining ETL/ELT pipelines (batch; streaming is a plus). Experience with at least one cloud data warehouse (e.g., Snowflake, BigQuery, Redshift, or similar). Strong instincts around data quality: schema design, validation, lineage, monitoring. Ability to talk directly with customers and internal stakeholders, gather requirements, and explain tradeoffs without hand-waving. Comfort in a fast-paced startup: ambiguity, context switching, and high ownership. Nice to Haves Experience with marketing / growth / revenue data (ad platforms, attribution tools, event data). Familiarity with tools like dbt, Airflow/Prefect, or similar orchestration / transformation frameworks. Experience managing API-based integrations (REST, OAuth, pagination, rate limits). Prior work in B2B SaaS onboarding / implementation or customer-facing technical roles. Basic understanding of ML / analytics use cases (MMM, incrementality tests, forecasting) and how data engineering supports them. Compensation & Benefits Compensation: competitive salary + meaningful equity — real ownership in BlueAlpha's success Benefits: health insurance, flexible PTO, and remote-friendly work Impact: work on multi-faceted problems end-to-end Culture: A collaborative, high-energy environment where we challenge ideas, not people — small team, big ambition How to Apply Ready to help define the future of AI-driven marketing? Send your resume and a short note to [email protected] .