Remote Data Engineer (Mid-Level)

Builth Wells; United States; Remote; USD 73,000 - 123,000; Full time

Job summary

Semble is seeking a Remote Data Engineer (Mid-Level) to build, test, and optimise the ELT pipelines powering our analytics and data products. This role offers ownership to contribute to the next generation of our platform, with remote options across France, the UK, and selected EU countries.

You will work with Databricks, Spark, Python and SQL to deliver reliable data. Ideal candidates have 3–5 years of experience and a solid grounding in lakehouse concepts.

Qualifications

• 3–5 years of data engineering experience
• Strong Python & SQL skills
• Experience with Apache Spark / PySpark
• Familiarity with lakehouse concepts
• Nice to have YAML exposure

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

Spark / PySpark

Pipeline monitoring

Tools

Databricks

Git

AWS

Great Expectations

Job description

Remote Data Engineer (Mid-Level)

2026-10-03T00:00:00

Builth Wells

Powys

GB

LD2 3

Any

2027-01-01T23:03:29.043

Are you looking to be part of something special, like shaping the future of healthcare? We are looking for a Data Engineer to help build, test, and optimise the pipeline powering our analytics, reporting, and data products. This is a role with real ownership to contribute to the next generation of our platform. If this sounds like you, keep reading!

At Semble, we are on a mission to enable health professionals to amplify their impact. We improve the way healthcare is delivered to millions of people by providing doctors and their teams with powerful, innovative, intuitive, and secure software. Our cloud-based clinical system is used by thousands of clinicians across the UK, France, and beyond—making their lives easier, saving them money, and structuring health data to support better care and research.

We are a passionate and driven team, proud to unite under strong cultural drivers:

• Impact - We do work that matters.
• Collaboration - We are in it together.
• Human touch - We care deeply.

This role can be based in France or the UK, or contracted in selected EU countries, full remote.

What you will be doing

• 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

What we're looking for

• 3-5 years of data engineering experience
• Strong Python & 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
• Nice to have: Exposure to YAML, Experience building analytics data models in Spark

What you'll get in return

• Autonomy and ownership — we’ll set the vision and share the context, then we trust you to run with things, which is why we hire you!
• Work alongside an inspiring team — our founders started Semble after a successful startup exit, and your future colleagues are all knowledgeable and innovators in their field.
• We welcome applications from people of all backgrounds and all walks of life, including underrepresented groups in the tech industry.
• We also encourage applications from disabled and neurodiverse candidates. If there are any adjustments we can make to support you throughout the recruitment process, please do let us know.