Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Platform Data Engineer

ASDA
Leeds
1 month ago
Applications closed

Related Jobs

View all jobs

DataBricks Data Engineer

Senior Data Scientist

Data Science Principal

Principal Data Engineer & Data Platform Leader (Hybrid)

Senior Data Engineer – Cloud & Data Platform (Hybrid)

Senior Principal Data Engineer – Platform Leadership

Job Title

Platform Data Engineer


Location

Asda House


Employment Type

Full time


Contract Type

Permanent


Hours Per Week

37.5


Salary

Competitive salary plus benefits.


Category

Data Science


Closing Date

8 November 2025


This role requires on-site presence at Asda House in Leeds for at least three days per week. We’re really looking forward to having you around!


We’re looking for a Platform Data Engineer to join our Platform Engineering team within the wider Data function.


In this role, you’ll help build, evolve, and support the shared data platform capabilities that power Asda’s analytical, operational, and streaming data products.


You’ll work closely with Data Engineers, Architects, and Product Managers across the data ecosystem to deliver scalable, secure, and cost efficient platform services enabling domain squads to deliver faster, more reliably, and with stronger observability.


You’ll also contribute to our engineering community of practice, driving continuous improvement, reusability, and high standards across everything we deliver.


Your Role (Key Responsibilities)



  • Design, build, and optimise platform-level data frameworks and pipelines in Databricks and Azure that underpin ingestion, transformation, and governance at scale.
  • Develop shared capabilities (e.g. ingestion framework, metadata capture, monitoring, FinOps dashboards, and operational observability tooling) that enable domain squads to self-serve.
  • Engineer for scale and reliability ensuring all pipelines and services are performant, cost‑efficient, observable, and compliant with platform security and governance standards.
  • Automate platform operations, reducing manual intervention through CI/CD, templated deployments, and reusable patterns.
  • Collaborate cross-functionally with Domain Data Engineers, Architects, and Platform Services (Infrastructure, Security, Power Platform) to ensure consistent design, performance, and integration across the ecosystem.
  • Contribute to cost observability and FinOps initiatives, instrumenting metrics at workspace, pipeline, and workload levels to drive optimisation and accountability.
  • Champion engineering best practices, including version control, code review, testing, observability, and documentation as part of our Agile Community of Practice.
  • Support platform reliability through proactive monitoring, alerting, and incident analysis across production and non-core environments.
  • Participate actively in Agile ceremonies, retrospectives, and technical design sessions to continuously improve our engineering culture and delivery processes.

About You (Experience & Qualifications)



  • Proven experience building and supporting data pipelines and frameworks at platform or enterprise scale.
  • Strong proficiency in Python, SQL, and PySpark, with a focus on performance, scalability, and modular design.
  • Hands‑on experience with Databricks, Azure Data Factory, Event Hubs, and Azure Data Lake Storage (ADLS).
  • Experience with streaming and batch architectures, including Delta Live Tables and Medallion design patterns.
  • Understanding of data governance, security, and access control including Unity Catalog, CMK encryption, Key Vault, and service principal management.
  • Familiarity with monitoring and observability tooling (e.g. logging, metrics, dashboards, alerts) and how to embed these into engineering solutions.
  • Experience contributing to CI/CD pipelines, infrastructure‑as‑code, and GitHub‑based workflows.
  • Understanding of FinOps principles and how to engineer for cost transparency and efficiency.
  • Strong collaborator with excellent communication skills, a problem‑solving mindset, and an eagerness to simplify, automate, and enable others.
  • Experience working within Agile delivery frameworks (Scrum, Kanban, or Lean) in a multi‑squad data organisation.

This position is open to flexible working / job share / part time working.


If you have any questions about the role, then please email


Everything you'll love

To ensure we balance moments where we know we need to collaborate together and the need for flexibility, Asda has a hybrid way of working with a minimum 3 days a week in one of our Home Offices. Over and above this, each area of Asda may have additional requirements which may require spending more days in the office, visiting suppliers, stores or depots.


You will also get an excellent benefits package including:



  • Discretionary company bonus
  • Company pension up to 7% matched
  • 15% colleague discount in store and online
  • Free access to wellbeing services such as Wagestream, 24/7 virtual GP, counselling, health and dental cash plans and a 24/7 employee assistance helpline, alongside discounts across a range of services and activities, from airport parking, enhanced to theme parks and cinemas.
  • Asda Allies Inclusion Networks – helping colleagues to make sure everybody is included and that our differences are recognised and celebrated
  • Excellent parental leave policies, including maternity & adoption leave, paternity leave, shared parental leave, neonatal care leave, and support for those doing fertility treatments.

We want all colleagues to be able to bring their best and true selves to work, every day. Simply put, we want our colleagues to be Proud to be Asda and proud to be themselves


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.