Data Engineer — Customer Data Science & Analytics

Marks and Spencer plc (UK); City of Westminster; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Colleague discount

Holiday entitlement

Discretionary bonus

Pension scheme

Life Assurance

Induction & training

Wellbeing support

Job summary

Marks & Spencer plc in London is seeking a data engineer to design, build and maintain robust data pipelines that support data science workflows. You will manage Airflow orchestration and work hands-on with the Databricks suite to deliver high-quality data engineering solutions for data science teams.

You will collaborate across teams, participate in code reviews on GitHub, and contribute to shared engineering standards while continuously learning in a fast-changing environment.

Qualifications

• Experience building robust data pipelines for data science workflows.
• Strong Airflow and Databricks experience.
• Experience collaborating with data scientists to enable delivery.
• Excellent cross-team communication.

Responsibilities

• Design, build and maintain robust, scalable data pipelines for data science workflows.
• Develop and manage complex Airflow orchestration for reliable pipelines.
• Work hands-on with Databricks to deliver data engineering solutions for data science teams.
• Collaborate via GitHub and follow engineering standards.
• Support data science delivery with proactive problem solving and root-cause analysis.
• Continuously learn and apply MLOps concepts where relevant.

Skills

Independent worker

Ownership

Delivery-focused

Communication

Tools

Airflow

Databricks

GitHub

Job description

Marks & Spencer plc in London is seeking a data engineer to design, build and maintain robust data pipelines that support data science workflows. You will manage Airflow orchestration and work hands-on with the Databricks suite to deliver high-quality data engineering solutions for data science teams.

You will collaborate across teams, participate in code reviews on GitHub, and contribute to shared engineering standards while continuously learning in a fast-changing environment.