Data Engineer
Summary
A 4-month contract Data Engineer role in hybrid London, building, maintaining and improving production batch ETL pipelines and large-scale datasets for a leading global technology company. Core stack: SQL, Python, distributed engines (Presto/Spark/Hive), Airflow, and Git-based workflows.
- Contract: 4 months
- Salary: £104,000 p.a. + bonus + paid annual leave & bank holidays
- Location: London - hybrid, 3 days onsite per week
We're hiring an experienced Data Engineer to join the data engineering team of a leading global technology company, supporting high-visibility products used at significant scale.
This is a hands-on engineering role focused on building, maintaining and improving production data pipelines and large-scale datasets. You'll join an established engineering team and work on clearly defined deliverables alongside experienced Data Engineers.
What you'll be doing
- Build, test and maintain production batch ETL/data pipelines
- Write and optimise SQL across large-scale datasets
- Use Python for data transformation and pipeline orchestration
- Maintain and improve existing pipelines, including backfills and schema changes
- Troubleshoot data-quality and pipeline issues
- Implement data-quality checks, testing and documentation
- Work with distributed data technologies such as Presto, Spark or Hive
- Use workflow orchestration tools such as Airflow
- Participate in code reviews and Git-based development workflows
- Collaborate with Data Engineers, Analysts and Engineering teams
The core work is production data engineering: ETL pipelines, large-scale SQL, pipeline changes, data-quality troubleshooting and code review.
What we’re looking for
- 5+ years' experience building production data pipelines
- Advanced SQL, including performance optimisation on large tables
- Strong Python for data engineering
- Experience with Presto, Spark, Hive or similar
- Experience with Airflow or another workflow scheduler
- Strong ETL/data pipeline development experience
- Git and code-review experience
- Strong understanding of data quality and accuracy
Experience with analytical data modelling, BI/dashboard or pipeline observability would be beneficial.
This is an opportunity to work on high-visibility, business-critical products with significant real-world impact, alongside a highly experienced engineering team.