Senior Data Engineer: GenAI & Automation (Remote EU/LATAM)

Lemon.io; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Lemon.io seeks a Senior Data Engineer to own GenAI-enabled data pipelines within a mature finance data platform. Remote from Europe or LATAM, the role is full‑time for 3 months with strong extension potential, balancing hands-on work (80%) and strategy (20%).

The position requires 6+ years in data engineering, deep Databricks experience, SQL/dbt, Python/PySpark, and production use of GenAI tools to automate monitoring and development.

Qualifications

• 6+ years of hands-on data engineering at senior or principal level.
• Strong Databricks experience at large scale.
• Strong SQL and dbt; Python / PySpark.
• Real, production use of GenAI 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.

Responsibilities

• Review pipelines, monitoring and releases with an as‑is → to‑be plan.
• Build agent‑based monitoring that detects failures and escalates automatically.
• Cut manual support effort from ~13–14 hours/day to ~2–3 hours/day.
• Speed up delivery on a complex data model with safer changes and testing.
• Bring agentic and AI‑assisted development into daily work and coach by example.
• Improve data quality visibility so issues are caught before business users see them.

Skills

Databricks

SQL

Python/PySpark

GenAI tools

Data quality

Finance data

Tools

dbt

GitHub

CI/CD pipelines

Job description

Lemon.io seeks a Senior Data Engineer to own GenAI-enabled data pipelines within a mature finance data platform. Remote from Europe or LATAM, the role is full‑time for 3 months with strong extension potential, balancing hands-on work (80%) and strategy (20%).

The position requires 6+ years in data engineering, deep Databricks experience, SQL/dbt, Python/PySpark, and production use of GenAI tools to automate monitoring and development.