Data Software Engineer - Python

Hdhe

London, United Kingdom2d ago

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Key details

Location
London, United Kingdom
Work style
Onsite
Level
Mid level
Job type
Full-time
Function
Software engineering
Focus area
other
Posted
2d ago

Skills

agileairflowawsazureazure data factoryci/cdcloud computingcode reviewscontainer orchestrationcontainerizationdata ingestiondata pipelinesdata warehousingdatabricksdbtdeployment automationdockerencryptiongithub actionsincident responseinfrastructure as codelakehousemlopsnetwork securitynew relicobservabilitypythonscrumsnowflakesqlstate managementterraformtest automationtroubleshootingxp

About the role

Data Software Engineer - Python

In a nutshell

We are looking for a strong python engineer who builds, tests, and maintains data platform capabilities that enable teams across Sainsbury's to leverage data and AI effectively. Implements infrastructure as code using Terraform and CI/CD pipelines via GitHub Actions to ensure reliable, repeatable deployments across data workloads. Does what they say they will do by delivering quality platform components and shows care for colleagues by creating well-documented, accessible solutions that make data engineering simpler and more efficient.

This is a hands-on engineering role requiring strong technical expertise, ownership of end-to-end delivery, and the ability to mentor other engineers and promote engineering best practices.

What I am accountable for

  • Build and maintain data platform capabilities including data ingestion pipelines, transformation frameworks (DBT), monitoring solutions, and governance controls following established patterns and technical standards.
  • Implement infrastructure as code using Terraform, deploying and managing cloud resources for data platforms across environments with guidance from senior engineers and adherence to configuration standards.
  • Develop and maintain CI/CD pipelines using GitHub Actions, implementing automated testing, deployment workflows, and operational automation for data pipelines.
  • Configure and maintain observability and monitoring using New Relic and other tools, implementing instrumentation, alerts, and dashboards for data pipelines and ML systems based on established patterns.
  • Contribute to platform capabilities that support data transformation (DBT), pipeline orchestration (Airflow/Astronomer), MLOps workflows including model versioning and deployment automation and much more
  • Support platform users including data engineers, ML engineers, data scientists, and analysts by troubleshooting issues, providing technical guidance, and creating clear documentation.
  • Participate in code reviews and knowledge sharing activities, learning from senior engineers and contributing to team capability through documentation and peer collaboration across data domains.
  • Identify and escalate technical debt, performance issues, and operational problems in data platforms, working with senior engineers to implement fixes and improvements.

  • Respond to incidents affecting platform services, supporting diagnosis and resolution of infrastructure issues, pipeline failures, and performance degradation under guidance from senior team members.

What I need to know

Essential

  • Strong programming skills in Python including package and environment management

  • Strong software engineering skills (experience of writing maintainable, tested code with proper error handling and documentation)

  • Strong proficiency in cloud platforms (AWS and/or Azure) with good understanding of data services, networking, and compute infrastructure

  • Strong SQL skills

  • Good working experience with infrastructure as code using Terraform, including resource creation, module usage, and state management

  • Familiarity with containerization (Docker) and basic container orchestration concepts

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