Data Engineer

Whitehall Resources Limited

Cambridge, UK

1 day ago

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Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

4 years minimum

Working hours

Regular working hours

Job source

www.careerjet.co.uk

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence JIRA Microsoft Azure Continuous Integration Information Engineering Data Governance Extract Transform Load (ETL) Data Systems Data Vault Modeling Iterative and Incremental Development IT Management

+24 more

Python (Programming Language) Power BI Standard Sql Search Technologies SQL Databases Tableau (Software) Unstructured Data Workflow Management Systems Enterprise Data Management Data Server Interface Enterprise Software Applications Microsoft Power Automate Large Language Models Multi-Agent Systems Generative AI Git Build Management Data Lakes AI Platforms Pyspark Kubernetes Data Pipelines Servicenow Databricks

Job description

We are seeking an experienced Data Engineer to design and deliver scalable, high-quality data solutions in Databricks. You will play a key role in evolving our enterprise data platform, creating trusted, AI-ready data products that power reporting, analytics, automation and AI across Enterprise IT. You will design and build modern data pipelines integrating enterprise platforms such as AI platforms including Microsoft Copilot, OpenAI and other enterprise AI services. The role will also contribute to our growing AI capabilities, engineering solutions for AI usage and adoption data, Retrieval-Augmented Generation (RAG), LLM integration and AI orchestration. Responsibilities:

Design, build and maintain scalable ETL/ELT pipelines using Databricks, PySpark, SQL and Python.
Design scalable data models using Data Vault principles.
Build trusted data products using Lakehouse and Medallion Architecture principles.
Integrate data from enterprise systems including ServiceNow, Jira, Azure DevOps and AI platforms such as Copilot and OpenAI.
Build data pipelines for AI usage, adoption, telemetry and performance analytics.
Design and implement RAG pipelines, including ingestion, embeddings, vector/semantic search and retrieval.
Integrate LLMs, APIs and enterprise data to support AI applications and agents.
Build and maintain AI orchestration workflows connecting models, data, tools and business processes.
Implement automated data quality, testing, monitoring and validation.
Optimise solutions for performance, scalability, reliability and cost.
Contribute to data governance, metadata, lineage, security and documentation.
Use Git and CI/CD to support automated and reliable deployment.

Requirements

Minimum 4 years’ data engineering experience, with strong experience in Databricks.
Strong Python, PySpark and SQL skills.
Experience designing scalable ETL/ELT pipelines and enterprise data models.
Strong understanding of Data Vault, Delta Lake, Lakehouse and Medallion Architecture.
Experience integrating enterprise systems through APIs and other data interfaces.
Experience working with structured and unstructured data.
Practical experience with Generative AI, RAG, embeddings, vector/semantic search and LLM integration.
Experience with AI or workflow orchestration, connecting models, data, APIs and tools.
Experience with automated data quality, testing and monitoring.
Experience with Git and CI/CD and good understanding of data governance and security.

Nice to Have Skills and Experience:

Experience with Microsoft Copilot, OpenAI/Azure OpenAI or Microsoft Graph.
Experience with Databricks AI capabilities, including Mosaic AI and Vector Search.
Experience with orchestration frameworks such as LangChain, LangGraph or Semantic Kernel.
Experience developing AI agents or agentic workflows.
Experience with Jira, ServiceNow or Azure DevOps data.
Knowledge of Power BI, Tableau or AI/BI.
Familiarity with Agile delivery and iterative development.
Strong communication and collaboration skills.