Full-Time

Data Engineer

Carnall Farrar

Carnall Farrar

No salary listed

London, UK

Hybrid

Hybrid role with one work-from-home day per week as standard and up to two days per week subject to client needs.

Category
Data & Analytics (1)
Required Skills
Agile
Python
Software Testing
Git
Apache Spark
SQL
Data Engineering
Data Modeling
Databricks
Requirements
  • 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.
  • Clear communication, knowing when to ask for support, and effective teamwork.
Responsibilities
  • 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 by keeping user stories and tasks up to date and contributing to stand-ups, retrospectives, and show-and-tells.
  • Flag early when work is deviating from plan and help identify and deliver mitigations.
  • Build an understanding of healthcare data and the CF lakehouse, including 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.
  • 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.
Desired Qualifications
  • Databricks lakehouse experience, including notebooks, Workflows and Jobs, and Delta Lake.
  • Unity Catalog basics.
  • Awareness of cloud basics such as storage and access control, and of medallion structure from bronze to silver to gold.
  • Exposure to dbt and basic dimensional modelling.

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Founded

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