Full job descriptionAfter clicking Apply, you’ll be invited to create a profile on the Via website to complete your application. This doesn’t guarantee you’ll be matched to this specific role - Via reviews every application (AI first, then a human checks the fit) and shortlists the right candidates. Your profile also stays active for other relevant roles on the platform, and stays anonymous until you match. It takes just a few minutes.
Car allowance: £6,000 per year
Location: London, WC2B 6SR
Working arrangement: Hybrid – minimum 2 days per week in the office
Employment type: Full-time
About the opportunityVia is partnering with a leading UK homeware retailer looking for a Principal Data Engineer to lead the development of its cloud-first data platform.
You’ll shape technical strategy, mentor senior engineers and build scalable data solutions supporting commercial, customer and operational decisions.
What you’ll be doing*Lead the design and development of modern cloud data platforms and pipelines
*Provide technical leadership, line management and mentoring to data engineers
*Drive data architecture, engineering standards and best practices
*Manage technical risks, delivery quality and platform performance
*Optimise cloud infrastructure costs and data processing efficiency
*Collaborate with product, engineering and data quality teams
What we’re looking for*6–8+ years’ experience in data engineering, including technical leadership
*Strong experience with Snowflake, Redshift or BigQuery (Snowflake preferred)
*Hands-on AWS experience, including S3, Lambda, Kinesis, SQS or Firehose
*Experience with dbt, Python or Node.js
*Advanced SQL and data modelling skills
*Experience with CI/CD, GitHub/GitLab and Terraform
*Proven ability to mentor and manage technical teams
Experience with Power BI, ThoughtSpot, automated testing, cloud cost optimisation or vendor management would be advantageous.
Why apply?*£6,000 car allowance
*Performance-related bonus
*Hybrid working
*Share save scheme
*Additional employee benefits
*Opportunity to shape enterprise-scale data engineering strategy