Senior Data Engineer at Scott Logic
Edinburgh EH3 9DN, , United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

20 Nov, 25

Salary

0.0

Posted On

21 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Azure, Sustainability, Private Healthcare, Cloud Services, Aws, Snowflake

Industry

Information Technology/IT

Description

About the role
Scott Logic is seeking experienced Data Engineers to design and deliver modern data solutions for major UK organisations and government departments. You’ll work on everything from building pipelines to integrating complex datasets, enabling advanced analytics, business intelligence, and AI.

Key responsibilities

  • Develop and optimise data pipelines, lakes, and warehouses.
  • Transform and model data to support reporting, insights, and machine learning.
  • Partner with clients to understand requirements and deliver practical solutions.
  • Provide technical direction, mentor colleagues, or lead project teams.
  • Ensure systems are well-structured, scalable, and maintainable.

What we’re looking for

  • Strong experience in data engineering: ingestion, transformation, storage, and reporting.
  • Skilled with tools such as Python, Spark, SQL, PySpark, Power BI (or comparable).
  • Solid software engineering background (JavaScript or similar experience a plus).
  • Strong communicator with a collaborative, problem-solving mindset.

NICE-TO-HAVE SKILLS:

  • Knowledge of AWS, Azure, or GCP cloud services.
  • Experience with Snowflake, Databricks, or CI/CD pipelines.
  • Worked within Agile teams and delivery environments.

What we offer

  • 25 days annual leave, increasing with length of service.
  • Pension plan, private healthcare, and life assurance.
  • Family-friendly leave policies.
  • Extra perks: gym discounts, cycle-to-work scheme, employee-led clubs/events.
  • Hybrid work model – remote flexibility plus in-person collaboration.
  • A values-driven company: we’re a certified B Corp, committed to diversity, equity, and sustainability.
Responsibilities
  • Develop and optimise data pipelines, lakes, and warehouses.
  • Transform and model data to support reporting, insights, and machine learning.
  • Partner with clients to understand requirements and deliver practical solutions.
  • Provide technical direction, mentor colleagues, or lead project teams.
  • Ensure systems are well-structured, scalable, and maintainable
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