Data Engineer

Taylor Rose Limited
Peterborough, United Kingdom
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Peterborough, United Kingdom

Tech stack

Artificial Intelligence
Data analysis
Confluence
JIRA
Customer Data Management
Data Governance
Data Infrastructure
Data Mapping
Data Migration
Python
Operational Databases
Cloud Services
Salesforce
SQL Databases
Tableau
Spark
Data Analytics
Data Management
Tools for Reporting
Interactive Whiteboards
Data Pipelines
Legacy Systems
Mulesoft
Databricks

Job description

  • 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 tolls such as Jira/Confluence/Miro

Requirements

Do you have experience in Tableau?, * Commercial experience as a Data Engineer in a modern data platform

  • Strong hands-on experience with Databricks (or equivalent cloud data platforms)
  • Proven experience building production data pipelines
  • 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

Benefits & conditions

  • 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.

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