Data Engineer - Databricks

Salary: £50K - £60K

Location: Manchester (3 days per week)

Role Overview

Our client is looking for a Data Engineer to take ownership of a Databricks platform and help push it into its next stage of maturity. This is a great opportunity for someone who enjoys more than just building pipelines. The role is focused on improving data quality, strengthening platform reliability, developing clearer Bronze, Silver and Gold data layers, and creating trusted datasets that can support reporting, analytics and wider business decision-making. You’ll be joining a business where data is becoming increasingly important, with the opportunity to shape how data is structured, governed and used across the organisation.

Key Responsibilities

• Maintain, improve and optimise an existing Databricks data platform.
• Build and enhance scalable data pipelines using Spark, SQL and Python or Scala.
• Develop and mature Bronze, Silver and Gold layers to support analytics, reporting and downstream data use.
• Ingest and integrate data from APIs, databases and other source systems.
• Design data quality rules, validation checks and exception reporting to improve trust in business data.
• Investigate data issues, identify root causes and implement fixes that prevent recurring problems.
• Work with analysts, BI developers and business stakeholders to understand data requirements and turn them into practical engineering solutions.
• Support the design of curated data models for reporting and analytical consumption.
• Monitor workflow performance, troubleshoot failures and improve the reliability of data processes.
• Contribute to better documentation, governance, naming standards, lineage and data access practices.
• Identify opportunities to automate, simplify and standardise data engineering workflows.

What We're Looking For

• Proven experience as a Data Engineer within a cloud‑based data environment.
• Strong hands‑on experience with Databricks and Apache Spark.
• Experience building or improving medallion architecture, including Bronze, Silver and Gold data layers.
• Strong SQL skills for transformation, validation and data analysis.
• Python or Scala experience for data engineering, automation or scripting.
• Experience extracting, ingesting and integrating data from APIs.
• Good understanding of data quality, data controls and reliability within production data environments.
• Experience working with cloud data services, ideally Azure, although AWS or GCP experience would also be relevant.
• Exposure to Delta Lake, Databricks Workflows, scheduling tools or lakehouse environments would be beneficial.
• An understanding of Power BI, reporting data models, governance, cataloguing or lineage would be useful.
• Strong communication skills, with the ability to work with technical and non‑technical stakeholders.

Why Consider This Role

This is a strong opportunity for a Data Engineer who wants more ownership, more influence and more impact than a standard pipeline‑focused role. You’ll be working on a business‑critical Databricks platform where data quality, structure and reliability genuinely matter. The business is investing in better data practices, so this role offers the chance to improve how data is ingested, transformed, monitored and made available to the wider organisation. It would suit someone who enjoys solving messy data problems, building robust engineering patterns and helping create a platform that people across the business can trust.