Data Platform Engineer - Databricks & Analytics Pipelines

  • Taylor Rose TTKW Limited
  • Peterborough, Cambridgeshire
  • 27/05/2026
Full time Information Technology Telecommunications SQL Python Testing CRM

Job Description

Responsibilities
  • Design, build, and maintain scalable, production grade data pipelines into Databricks.
  • Implement ingestion, transformation, and optimisation patterns using SQL, Spark, and Python.
  • Ensure datasets are performant, reliable, and analytics ready.
  • Lead hands on data mapping from legacy systems into Databricks with downstream implication with Analytics (Tableau) and strong AI use cases (Mulesoft IDP and Data360/Agentforce).
  • Support ingestion and harmonisation of data arising from M&A activity.
  • Analyse acquired datasets and integrate them into the central data platform.
  • Establish and govern testing standards covering functional, regression, integration and UAT testing.
  • Implement data quality checks, validation rules, and monitoring within pipelines.
  • Support governance standards defined by the Data & Analytics Manager.
  • Ensure high quality documentation and data governance.
  • Work with internal and external teams, using Agile delivery and Project Management tools such as Jira/Confluence/Miro.
Requirements
  • Commercial experience as a Data Engineer in a modern data platform.
  • Strong hands on experience with Databricks (or equivalent cloud data platforms).
  • Experience mapping and migrating data from legacy systems.
  • Solid understanding of data modelling and transformation.
  • Experience supporting analytics tools such as Tableau.
  • Desirable: Experience with Salesforce Data Cloud (Data 360) or CRM data models.
  • Desirable: Exposure to AI ready data platforms or automation use cases.
  • Desirable: Experience working within a Centre of Excellence or multi team environment.
Success Measures
  • Reliability of data pipelines (uptime, successful run rates).
  • Time taken to onboard new data sources.
  • Reduction in downstream data issues and rework.
  • Adoption of engineered datasets by analytics and AI use cases.
  • Quality and clarity of data documentation and mappings.
Core Values
  • Aspire: Challenge convention, be entrepreneurial with energy for change. Be the best we can be.
  • Innovate: Creatively evolve our working practices, use our revenue and resources in a virtuous cycle of improving our people, systems and growth.
  • Integrate: Bring together people and systems into a cohesive force.
  • Commitment: Work with integrity and invest in long term relationships, creating a strong market position and delivering sustained commercial advantage.
Equality and Diversity

This organisation strives to operate a policy of equal opportunity and to not discriminate against any person because of sex, race, colour or national origin.