Data Engineer (ETL/ELT) – Remote

About the role

We are looking for an experienced Data Engineer to design, build, and maintain robust data pipelines that support both batch and streaming workloads. The role is fully remote with occasional travel to client sites, and you will work closely with machine‑learning, product, and analytics teams to deliver high‑quality data assets.

Key responsibilities

• Develop and operate end‑to‑end ETL/ELT workflows using Python and SQL on platforms such as Databricks and Spark.
• Design, schedule, and monitor data pipelines with orchestration tools like Airflow, Dagster, Luigi or Prefect.
• Model, version, and manage structured data assets in Delta Lake, Parquet, or Iceberg formats.
• Implement data quality checks, schema enforcement, and audit logging to ensure compliance.
• Collaborate with ML and AI teams to provide clean, well‑documented datasets for model training and production.
• Continuously evaluate and adopt new tools and best practices to improve the data platform.
• Optimize performance and cost across compute, storage, and orchestration resources.

Required profile

• 3–6 years of professional experience as a Data Engineer or ETL Developer.
• Strong proficiency in Python and SQL.
• Hands‑on experience with Databricks, Spark, or comparable big‑data frameworks.
• Familiarity with modern data lakehouse architectures (Delta, Parquet, Iceberg).
• Experience working in cross‑functional teams alongside ML, product, and analytics stakeholders.

Required skills

• Python
• SQL
• Databricks
• Apache Spark
• Airflow
• Dagster
• Luigi
• Prefect
• Delta Lake
• Parquet
• Iceberg
• CI/CD pipelines
• GitHub Actions