Job Opportunities API

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  Requirements 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 a