Senior Data Engineer – Gen AI & Automation (Databricks, Finance Data) – full-time, 3 months + strong potential to extend

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Remote: Europe or LATAM
A role for a Senior, hands-on Data Engineer who uses agentic AI to transform how a mature finance data team works. The client is one of the world's leading home appliance manufacturers.
The context
The Global Finance data platform serves thousands of users, with reports followed at CFO and CEO level. Pipelines run hourly around the clock across APAC, India, Europe and Oceania, and core models process around 3 billion records where every figure must match exactly. The team is strong but absorbed by operations, especially at month-end close. This is not a greenfield role — your job is to automate that load away and set a new standard by example. Roughly 80% hands‐on, 20% strategy.
Your first 3 months Review pipelines, monitoring and releases, and present an as‐is → to‐be plan with about 5 concrete deliverables
Build agent‐based monitoring that detects failures and delays, applies rule‐based fixes and escalates automatically
Cut manual support effort (today ~13–14 hours/day, target ~2–3 hours/day)
Speed up delivery on a complex, interdependent data model with safer changes, better testing and impact analysis
Bring agentic and AI‐assisted development (e.g. Databricks agents, Git Hub Copilot)



into the team's daily work and coach by example
Improve data quality visibility so issues are caught before business users see them Beyond 3 months
Grow into the technical go‐to person for the Finance innovation team, designing multi‐agent workflows in Databricks to automate finance business processes. xghoner
Must-haves 6+ years of hands‐on data engineering at senior or principal level
Strong Databricks experience at large scale
Strong SQL and dbt; Python / Py Spark
Real, production use of Gen AI and agentic tools — agents for monitoring, automation or dev workflows (not just experiments)
Production experience with pipeline monitoring, observability and data quality
A proven before/after track record improving an existing, mature platform
Experience with large, high‐precision datasets
Finance data experience (month‐end close, P&L;, sales and accounting data)
Based in Europe or LATAM, able to work full CET hours; fluent English Nice‐to‐haves SAP as a data source (FI/CO, sales data) — strongly preferred
Databricks AI features (Mosaic AI / Agent Bricks, Unity Catalog)
Medallion architecture / Data Mesh, CI/CD and Git Hub
Power BI / semantic models; large enterprise experience Hiring process Call with the Head of Finance Data & Analytics
Technical call with a senior data engineer from the team The selected candidate goes through an insider list and legal onboarding, as the role involves confidential financial data.

📌 Senior Data Engineer – Genai (Arenas de Iguña)
🏢 lemon.io
📍 Arenas de Iguña