Data Engineer (FTC) | London, EC2M

About LPPI

One of the key priorities at LPPI is ensuring that our people work daily in an empowered, supportive, diverse, and inclusive culture. Practically, this means recognising and valuing the uniqueness of every individual in terms of background, experience, beliefs, and circumstances. This starts with the recruitment process, where we partner with agencies that share our common goal and advertise on a variety of job boards to access the broadest spectrum of candidates.

Once successful applicants are on board, we trust our people to work in the way that works best for them, which typically involves a mix of office and home working, alongside an engagement model to ensure frequent two-way feedback.

We are very proud of our culture at LPPI and the benefits it brings to both our people and the business. But don’t just take our word for it! Recently, we invited our entire workforce to describe in three words what is great about us, and they said—our people, flexibility, and collaboration.

If you would like to join a company that is inclusive and forward-thinking, please read on.

Role Purpose

The purpose of this role is to solicit proposals from qualified vendors to supply a Data Engineer position that aligns with LPPI’s purpose by supporting the delivery of innovative, supportable, and sustainable solutions that help LPPI achieve its vision of being a leading provider of pensions and investments.

This role is an 8-month fixed-term contract.

Key Responsibilities

• Ensure business-as-usual (BAU) deliverables, including:
  • Systems and processes (including documentation)
  • Strategic priorities
  • Specific approval authorities
  • Team management
  • Compliance with relevant regulations
  • Financial control
• Provide commercial project experience in delivering modern data solutions, specialising in Medallion Architecture and expertise in:
  • Technical Stack (Must-Have):
    • Medallion, Delta Lake, and metadata-driven architecture using Microsoft Fabric or Synapse Analytics ETL pipelines
    • Data transformation using SQL (query language) and Python notebooks
    • Data storage and warehousing using:
      • SQL databases
      • Delta Lake (Gen2)
      • Snowflake
    • Dimensional modelling using the Kimball methodology
    • Power BI Interactive Dashboards and Paginated Reports using:
      • DAX functions
      • Power Query
  • Work closely with business analysts and stakeholders to understand data requirements
  • Create technical specifications and architecture visions covering:
    • Quality attributes
    • Associated risks
    • Technical and system requirements
  • Collaborate with the wider Data Team and Business Analysts to align data models with business needs
  • Design, build, and maintain robust ETL pipelines for extracting data from diverse sources (e.g., APIs, databases, files)
  • Use Azure Git Repos, boards, and CI/CD deployment pipelines for version control of ETL, SQL, and reports
  • Transform and load raw data into structured formats using:
    • Business rules
    • Data cleansing and enrichment techniques
    • Unified schemas
  • Design and implement reporting data models (e.g., star/snowflake schemas) to support analytics
  • Optimise ETL activities for efficiency and scalability by:
    • Data indexing
    • Partitioning
    • Parallel processing strategies to reduce latency and improve throughput
  • Implement data validation rules and cleansing routines to ensure accuracy and consistency
  • Monitor data pipelines for anomalies, errors, and performance issues
  • Implement access controls and encryption where necessary
  • Document:
    • ETL processes
    • Data flows
    • Transformation logic for transparency and maintainability
  • Develop interactive, visually compelling Power BI reports and dashboards tailored to business needs
  • Hold the DP-203: Data Engineering on Microsoft Azure certification (or an equivalent).
  • Any additional certifications/courses in Gen AI would be beneficial.