Data Engineer

About the role

About us We are a leading consultancy with a purpose to make an enduring impact on health and healthcare. We work with leaders and frontline teams to improve health, transform healthcare, drive adoption of innovation and create value through investment. Our consultancy serves the entire healthcare sector, from payors and providers of care, to life science companies, health tech and sector suppliers and health investors. We provide end-to-end services, from strategy through implementation, accelerated by data, digital and AI. We shape opinion through evidence-based thought leadership on key issues affecting health. With unmatched ability to access and use health data, our consultants are a driving force for delivering positive and meaningful change. About the role The Data Engineer sits within the Data Innovation team and works day-to-day on the CF lakehouse, our Databricks platform that holds the routine healthcare data behind our analytical and product work. The role is hands-on and delivery-focused: writing SQL and Python, building and maintaining automated pipelines, and turning raw data into structured, production-ready material that consultants and clients can rely on. CF runs an apprentice model of development. You will learn actively from senior engineers, contribute to the team's collective knowledge, and take on greater scope as you grow. The work spans data cleansing and validation for client engagements, building and maintaining pipelines, and contributing to CF's technical products, including through hackathons. This is a good fit for an engineer with a couple of years of experience who wants to build a broad technical foundation in a data-rich healthcare consultancy, work close to real client problems, and see how technical work turns into client value. Responsibilities The requirements, responsibilities and duties of the role will include, but are not limited to: Engineering and delivery Build and maintain automated data pipelines using PySpark and Spark, with appropriate monitoring Build data models and pipelines under the guidance of senior colleagues, producing production-ready code or client-ready material Develop data quality, validation and consistency checks, and carry out data cleansing Develop unit, functional and integration tests, and follow the team's Git and GitHub workflow Participate in agile ways of working: keep user stories and tasks up to date, and contribute to stand-ups, retros and show and tells Flag early when work is deviating from plan, and help identify and deliver mitigations Domain, clients and collaboration Build an understanding of healthcare data and the CF lakehouse: what is collected, how it is structured, and how new sources are brought in Work with teams to bring analytical insights to client problems Communicate technical solutions to non-technical colleagues, and give and receive feedback well Learning and contribution Learn best-practice development processes from senior colleagues, and seek out new tools and techniques to apply Use AI tools to improve code quality and efficiency Support business development and bid writing on technical detail, and contribute to product development through hackathons and thought leadership The requirements of the role include: Around 2 to 3 years of experience in a data engineering or comparable technical data role Working SQL, used day-to-day on the lakehouse Intermediate Python for data transformation and automation Experience building automated data pipelines using PySpark or Spark, with appropriate monitoring Ability to write unit, functional and integration tests Comfort working to a Git and GitHub workflow Curiosity about healthcare data and how it relates to care delivery and policy A clear communicator who knows when to ask for support and works well in a team Desirable, and not expected on day one: Databricks lakehouse experience: notebooks, Workflows and Jobs, Delta Lake Unity Catalog basics (we will train) Awareness of cloud basics such as storage and access control, and of medallion structure, bronze to silver to gold Exposure to dbt and basic dimensional modelling Flexible working We follow a hybrid working model that balances in person connections and remote work to drive exceptional client impact. We enjoy working in person together with clients and colleagues and work where clients need us to be. In supporting flexibility and remote working, team members can work from home one day per week as standard. Additionally, we offer 44 remote working days per year which can be used to top up your working from home days and enable you to work from home up to two days per week-subject to client needs. Alternatively, you could use your allowance in blocks to manage school holidays or other commitments. Our core in person working hours are from 10am until 4pm allowing you that extra flexibility to manage your schedule in a way that works for you. Our commitment to Diversity & Inclusion We are committed to building an i

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