Data Engineer (FTC)

One of the key priorities at LPPI is ensuring that our people work every day 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 plus 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. 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 document is to solicit proposals from qualified vendors to supply a practical Data Engineer role 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

• Include business as usual deliverables, e.g. systems and processes (including documentation), strategic priorities, specific approval authorities, team management, compliance with relevant regulations and financial control.
• Commercial project experience in delivering modern data solutions using Medallion Architecture.
• Work closely with business analysts and stakeholders to understand data requirements.
• Creation of technical specifications and architecture visions covering quality attributes, diagrams, associated risks, and technical and system requirements.
• Collaborate with the wider Data Team and Business Analysts to align data models with business needs.
• Build and maintain robust ETL pipelines to extract data from diverse sources (e.g. APIs, databases, files).
• Use Azure Git Repo, Boards and CI/CD deployment pipelines for version control of ETL, SQL & Reports.
• Transform and load raw data into structured formats using business rules, data cleansing and enrichment techniques into a unified schema.
• Design and implement reporting data models (e.g. star/snowflake schemas) to support analytics.
• Tune ETL activities for efficiency and scalability through data indexing, partitioning, as well as parallel processing strategies to reduce latency and improve throughput.
• Implement data validation rules & 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, and transformation logic for transparency and maintainability.
• Design and build interactive, visually compelling Power BI reports and dashboards tailored to business needs.

Technical Stack (Must Have)

• Medallion, Delta Lake and metadata‑driven architecture using MS Fabric or Synapse Analytics.
• ETL pipelines.
• Data Transformation using SQL Query Language and Python notebooks.
• Data storage and warehouse using SQL DB, Delta Lake (Gen2), Snowflake.
• Dimensional modelling using Kimball methodology.
• Power BI Interactive Dashboard and Paginated Reports using DAX functions and Power Query.
• DP-203: Data Engineering on Microsoft Azure or an equivalent certification. Additional certification/courses in the use of Gen AI will be beneficial.

Requirements for the Role

• A familiarity in Investment Management and/or Financial Services.
• Commercial experience working with business stakeholders within a cross‑functional matrix environment.
• Experience in the delivery of projects utilising Agile methodologies.
• Must be able to understand and apply new technologies to stay current with best practices and trends in application and data architecture for financial services.
• Experience in handling, interpreting, and presenting complex numerical data and technological challenges in a clear and concise manner.
• Self‑motivated, decisive, with the ability to adapt to change and competing demands.
• Experience working both independently and within a team‑oriented, collaborative environment.
• Adept at conducting research into project‑related issues and products.
• A proactive, self‑motivated team player who can manage a high workload with multiple deadlines and continually strive for improvements in quality, efficiency and presentation.
• Bachelor’s degree in computer science, engineering, or a related field (or equivalent experience).
• Maintain a working technical understanding of the complexities in delivering change into an Investment Management organisation, specifically where the application eco‑system is decentralised.
• Good conduct that is consistent with the LPPI values- aligned behaviours.

Reasonable adjustment will be made to working arrangements to accommodate a person with a disability who otherwise would be prevented from undertaking the work.