ETL Developer – Data Engineer (Remote)

About the role

We are looking for an experienced ETL Developer to join our data engineering team on a remote basis. You will design, build, and maintain robust data pipelines that feed machine‑learning and analytics initiatives across the organization.

Key responsibilities

• Build and operate data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Dagster.
• Develop ETL/ELT workflows in Python and SQL for both batch and streaming workloads.
• Collaborate with ML and AI teams to deliver high‑quality datasets for training and production.
• Model and maintain structured data assets (Delta, Parquet, Iceberg) with versioning and lineage tracking.
• Implement orchestration, scheduling, monitoring, and automated recovery for pipeline jobs.
• Ensure data quality and compliance through validation frameworks, schema enforcement, and audit logging.
• Contribute to data platform evolution by evaluating tools, standardising best practices, and improving developer experience.
• Support performance and cost optimisation across compute, storage, and orchestration systems.

Required profile

• 3–6 years of experience as a Data Engineer or ETL Developer in a production environment.
• Strong proficiency in Python and SQL.
• Hands‑on experience with Databricks, Spark, or comparable big‑data frameworks.
• Familiarity with workflow orchestration tools such as Airflow, Dagster, Luigi or Prefect.
• Deep understanding of data modelling, data warehousing, and distributed processing.
• Knowledge of modern lakehouse architectures (Delta, Parquet, Iceberg).
• Experience with CI/CD pipelines, GitHub Actions, and data‑pipeline testing frameworks.
• Ability to work cross‑functionally with ML, product, and analytics teams.

Required skills

• Python
• SQL
• Databricks
• Apache Spark
• Airflow
• Dagster
• Luigi
• Prefect
• Delta Lake
• Parquet
• Iceberg
• CI/CD
• GitHub Actions
• Data pipeline testing frameworks