Data Engineering Support Engineer

Block MB
City of London
1 week ago
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Data Engineering Support Engineer

Salary: £55,000 - £60,000

Location: London, Hybrid


Overview

We’re looking for a Data Engineering Support Engineer to help keep our data pipelines and products running smoothly. This is a hands‑on role focused on PySpark and SQL, working mostly on existing jobs rather than building greenfield products.

You’ll investigate and fix bugs in our data workflows, improve reliability and performance, and be the first technical point of contact when something breaks. If you can write your own code and small features, even better – but the core of the job is support, stability and quality rather than product ownership.


What you’ll do

  • Monitor existing PySpark and SQL data pipelines, jobs and scheduled workflows.
  • Investigate production issues, identify root causes, and fix bugs in existing code and configurations.
  • Validate data outputs, write ad‑hoc SQL queries, and ensure data quality and completeness.
  • Work closely with Data Engineers and Analysts to triage tickets, prioritise fixes and communicate status.
  • Make small enhancements to existing jobs (e.g. performance tweaks, new columns, minor transformations) where needed.
  • Document fixes, update runbooks, and suggest improvements to monitoring and alerting.


What we’re looking for

  • Solid experience with PySpark (or Spark with Python) and strong SQL skills.
  • Experience working with existing data pipelines, ETL jobs or batch processes (investigating and fixing issues rather than only building new systems).
  • Comfortable reading other people’s code, understanding complex logic, and making safe changes.
  • Ability to write clean, maintainable code in Python; familiarity with version control (e.g. Git).
  • Strong debugging mindset, attention to detail and a structured approach to problem‑solving.
  • Good communication skills and the ability to work with engineers, analysts and non‑technical stakeholders.


Nice to have

  • Experience with job schedulers or orchestration tools (e.g. Airflow, Databricks Jobs, similar).
  • Exposure to cloud data platforms (AWS, GCP or Azure).
  • Experience in a data support, application support or production operations‑style role.

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