Data Engineer

Principle; City Of London; Hybrid; GBP 88,000 - 120,000; Full time

Job summary

Principle is hiring an experienced Data Engineer in London. You will build production batch ETL pipelines, write SQL on large datasets and transform data with Python. You’ll implement data quality checks and work with Presto, Spark or Hive, using Airflow for orchestration.

You’ll join a skilled engineering team delivering high-impact data products. The role focuses on production data pipelines, schema changes, troubleshooting and code reviews within a hybrid London environment, collaborating

Qualifications

• 5+ years of experience building production data pipelines.
• Advanced SQL with performance optimisation on large tables.
• Experience with Presto, Spark, Hive or similar.
• Experience with Airflow or another workflow scheduler.
• 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

SQL

Python

ETL pipelines

Data quality

Airflow

Presto

Spark

Hive

Git

Code reviews

Tools

Airflow

Git

Job description

• 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
• Experience with Presto, Spark, Hive or similar
• Experience with Airflow or another workflow scheduler
• 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.