Senior Data Engineer

Mirai Talent; Manchester; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Mirai Talent partners with a disruptive FinTech in Manchester to hire a Senior Data Engineer. You’ll help build a Databricks-native data platform and support production data pipelines in a hybrid, two-days-in-office model.

The role welcomes engineers from Data Engineering, Platform, DevOps or Systems Engineering backgrounds with strong data foundations, Python, SQL/Spark, and API/data integration skills.

Qualifications

• Strong Databricks and data engineering fundamentals.
• Proficiency in Python, SQL, and Spark.
• Experience with ETL/ELT pipelines and data warehousing.
• Knowledge of CI/CD, testing, and deployment.
• Background in Azure data services and governance.

Responsibilities

• Build and evolve a Databricks-native data platform.
• Ingest, transform and orchestrate high-volume data.
• Develop production ETL/ELT pipelines and APIs.
• Collaborate with Data Science to enable ML/AI workflows.
• Ensure platform reliability, security, and governance.

Skills

Databricks

Python

SQL

Spark

ETL/ELT

APIs

CI/CD

Azure

Data warehousing

Education

STEM background

Tools

Terraform

Bicep

Playwright

Selenium

Unity Catalog

Lakeflow

Lakebase

Job description

Manchester | Hybrid, ideally 2 days per week in office

We’re working with a truly disruptive FinTech that is continuing to invest heavily in its data and technology capability.

With a growing Data Science function and around 3–5TB of new data being processed each week, they’re looking for a Senior Data Engineer to help build and evolve the platform behind it.

This isn’t necessarily a traditional Data Engineering profile. They’re open to people from Data Engineering, Platform, DevOps or Systems Engineering backgrounds, but strong data foundations and hands‑on Databricks experience are key.

The role

You’ll work within a cross-functional team, helping continue the move towards a Databricks‑native environment and building reliable, scalable data and platform capabilities.

You’ll be working across:

• Databricks, Python, SQL and Spark
• High-volume data ingestion and transformation
• Production ETL/ELT pipelines
• APIs, SFTP/FTPS and automated data retrieval
• CI/CD, automated testing and deployment
• Platform reliability, monitoring and troubleshooting
• Azure infrastructure, security and governance
• Data Science, ML and increasingly agentic workflows

The focus is production engineering rather than building AI models, creating the foundations that allow Data Science and automated workflows to operate effectively.

What we’re looking for

Databricks is the big one. Alongside that, we’re looking for strong Python, SQL/Spark and ETL/ELT experience, good knowledge of databases and data warehousing, including dimensional/Kimball principles, plus an understanding of platform, DevOps and systems engineering.

They also value genuine technical curiosity. If you keep up with new technology, experiment with AI/deep learning or have side projects outside your day job, they’ll want to hear about them.

A STEM background is beneficial, but not essential.

Nice to have

• Databricks Asset Bundles, Lakeflow Jobs/Pipelines, Unity Catalog, Volumes and/or Lakebase
• Agentic or AI-enabled engineering workflows, LLM integrations or AI coding tools
• Playwright/Selenium
• Terraform/Bicep
• Scala, PowerShell and YAML

The team

You’ll join a highly technical, collaborative team working closely with a growing Data Science function. Ideally you’ll spend around two days per week in the Manchester office, but it’s an output-driven environment with plenty of autonomy.

Diversity & Inclusion

We welcome applications from people of all backgrounds and experiences. If the role interests you but you don’t tick every box, we’d still encourage you to apply. Different experiences, perspectives and routes into technology are valued.