WGSN

Senior Data Engineer

WGSN

full-time

Posted on:

Location Type: Office

Location: London • 🇬🇧 United Kingdom

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Job Level

Senior

Tech Stack

AirflowAWSCloudDockerETLGoogle Cloud PlatformLinuxNumpyPandasPySparkPythonSQL

About the role

  • Design, develop, and maintain scalable data architectures across Snowflake, Databricks, and cloud environments
  • Lead schema design, dimensional modelling, and query optimisation to support high-performance analytics and AI workloads
  • Collaborate with senior data scientists to structure data for classification, forecasting, embedding generation, and multimodal workflows
  • Own complex SQL development and performance tuning across DS&E and DPS teams
  • Optimise costly queries, improve warehouse efficiency, and ensure best-practice SQL standards across shared codebases
  • Build robust ETL/ELT pipelines for ingestion, transformation, validation, and delivery
  • Develop resilient ingestion workflows for external APIs
  • Implement pipelines using Snowpark, PySpark, and distributed compute environments
  • Apply Snowflake performance optimisation, cost governance, RBAC, and Snowflake best practices
  • Ensure high standards of data accuracy, completeness, and reliability
  • Build automated CI/CD workflows for data using GitHub Actions, CircleCI, or similar
  • Build and maintain orchestration workflows using Airflow, Prefect, Dagster, or equivalent
  • Run, log, monitor, and debug workloads across VMs, Docker containers, and cloud compute environments
  • Provide guidance to junior engineers and contribute to building team-wide engineering maturity

Requirements

  • 5+ years of hands-on experience as a Data Engineer
  • Proven success designing and scaling production-grade data pipelines in cloud environments
  • Experience mentoring junior engineers or contributing to capability uplift across teams
  • Expert-level SQL: complex queries, optimisation, performance tuning, analytical SQL
  • Advanced data modelling (star schemas, normalisation, dimensional modelling)
  • Strong Python skills, including Pandas, NumPy, and PySpark/Snowpark
  • Experience with Snowflake (performance optimisation, cost management, RBAC, governance)
  • Experience with Databricks, distributed compute, and PySpark
  • Data pipeline orchestration (Airflow, Dagster, Prefect)
  • Data validation frameworks (e.g., Great Expectations)
  • Strong familiarity with cloud platforms (AWS or GCP)
  • Experience building resilient API ingestion pipelines
  • Understanding of Docker, Linux servers, and cloud VMs
  • DataOps & DevOpsCI/CD workflows for data pipelines (GitHub Actions, CircleCI)
  • Logging, monitoring, observability for data workflows
  • Excellent communication across technical and non-technical teams
  • Ability to work within and contribute to cross-functional pods (DS + DE + Product + Content)
  • Strong problem-solving skills and ownership mindset
Benefits
  • 25 days of holiday per year - with an option to buy/ sell up to 5 days
  • Pension, Life Assurance and Income Protection
  • Flexible benefits platform with options including Private Medical, Dental Insurance & Critical Illness
  • Employee assistance programme, season ticket loans and cycle to work scheme
  • Volunteering opportunities and charitable giving options
  • Great learning and development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
SQLdata modellingPythonPandasNumPyPySparkSnowparkETLdata validationdata pipeline orchestration
Soft skills
communicationproblem-solvingmentoringownership mindsetcollaboration