Data Engineer

Principle HR; City Of London; Hybrid; GBP 94,000 - 114,000; Part time

Job summary

Principle HR in London is hiring an experienced Data Engineer to join our data engineering team, supporting high-visibility products at scale.

This hands-on role focuses on building, maintaining and improving production data pipelines and large datasets. You will collaborate with engineers and analysts to deliver reliable, well-documented data infrastructure in a hybrid London setup.

Qualifications

• 5+ years of 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.

Responsibilities

• 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.

Skills

5+ years exp

SQL

Python

Presto

Spark

Hive

Airflow

ETL

Git

Data quality

Tools

Presto

Spark

Hive

Airflow

Git

Job description

• 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.