Data Engineer - Unique NFP at hireful
London KT1 4DQ, , United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

15 Jun, 25

Salary

0.0

Posted On

15 Mar, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Aws, Python, Sql, Azure

Industry

Information Technology/IT

Description

Do you have experience as a Data Engineer? If you have we have a great opportunity for people looking to leave the rat race to work in an amazing environment. It’s a unique organisation that can offer an amazing pension (11%) an fantastic work environment (excellent glassdoor reviews / very flexible) and truly unique historic beautiful surroundings to work in? I’ve worked with them for years and people really do love it there and stay!
Role - Data Engineer
Salary c. 50K + 11% Pension + Bonus + Some amazing benefits - Salary review pending 1st April
Location - SW London / Surrey borders - 2 days Office

YOU WILL REQUIRE EXPERIENCE OF MOST OF THE FOLLOWING

  • Proficiency in SQL and Python, with proven experience developing and optimising ETL/ELT pipelines in large-scale environments.
  • Experience with data warehousing tools (e.g. Snowflake, Amazon Redshift Azure Synapse) and cloud platforms like Azure, AWS, or GCP.
    Unique opportunity to a great charity with a truly global brand.
Responsibilities

THE ROLE

You will be joining a brand new data team working on a greenfield project setting up a new data platform for the charity looking at pooling information across Data Silos into a brand new Cloud based Data Warehouse.

KEY TASKS WILL INCLUDE

  • Design, build, and maintain ETL/ELT pipelines to integrate data from multiple systems.
  • Lead the implementation and optimisation of the data warehouse, ensuring high performance and scalability.
  • Contribute to the design and evolution of the data warehouse architecture, working closely with the data manager to ensure alignment with organisational needs.
  • Collaborate with the Data Manager and Analyst to enforce data governance standards and develop advanced analytics models.
  • Continuously test and optimise data pipelines, applying best practices in CI/CD.
  • Manage the data infrastructure codebase using version control systems like GitHub
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