Remote Data Engineer: ELT Pipelines & Databricks

Forest Row; United States; Remote; USD 79,000 - 119,000; Full time

Benefits offered by this job

Autonomy and ownership

Inspiring team

Diversity and inclusion

Adjustments during recruitment

Job summary

Forest Row is hiring a Remote Data Engineer (Mid-Level) to build, test, and optimise our data pipelines powering analytics, reporting, and data products. This role offers real ownership to contribute to the next generation of our platform in healthcare software.

Based in the UK, France, or selected EU countries with full remote work, you will develop ELT pipelines, deploy Databricks workflows, and collaborate with data and product teams to deliver reliable, well-tested data.

Qualifications

• 3–5 years of data engineering experience.
• Strong Python and SQL skills.
• Experience with Apache Spark / PySpark.
• Ability to monitor, troubleshoot and resolve pipeline failures.
• Familiarity with lakehouse concepts.
• Experience with Git, Databricks, streaming / CDC, AWS, Great Expectations.

Responsibilities

• Build and maintain ELT pipelines, monitor pipeline health and data freshness.
• Write and maintain config-driven pipeline definitions and deploy workflows to Databricks across a multi-tenant environment.
• Extend our modelling layer, support CI/CD and ingestion projects.
• Collaborate with data and product teams to deliver reliable, well-tested data.
• Participate in code reviews and help evolve platform standards and documentation.

Skills

Python

SQL

Data engineering

Tools

Spark / PySpark

Databricks

Git

AWS

Great Expectations

Streaming / CDC

YAML

Job description

Forest Row is hiring a Remote Data Engineer (Mid-Level) to build, test, and optimise our data pipelines powering analytics, reporting, and data products. This role offers real ownership to contribute to the next generation of our platform in healthcare software.

Based in the UK, France, or selected EU countries with full remote work, you will develop ELT pipelines, deploy Databricks workflows, and collaborate with data and product teams to deliver reliable, well-tested data.