Senior AWS Data Engineer (Fixed Term Contract)

Senior AWS Data Engineer (Fixed Term Contract)

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Join Microlise as aSenior AWS Data Engineer on a 12-month fixed term contract and help build thedata foundations behind the next generation of customer-facing analytics and AI products.

This is a hands-on engineering role in a major cloud data platform programme, where you’ll help turn operational, telematics, customer and third-party data into trusted, reusable data products that power dashboards, APIs, self-service analytics, machine learning and future generative AI services.

You’ll work with modern AWS managed services, lakehouse architecture, Data Mesh principles and governance-by-design patterns to create data that is reliable, discoverable, secure and ready for real customer impact.

If you enjoy building robust data platforms, solving complex integration problems and shaping how data enables better products, this is an opportunity to do meaningful engineering work that will be reused across the Microlise product portfolio.

What You’ll Be Doing

Make a visible impact on customer-facing analytics and AI

Microlise is investing in an Analytics and AI platform that connects data across multiple complex operational systems and third-party sources. Your work will help make that data trusted, governed and easy to reuse, enabling faster analytics delivery, richer customer insights, API-driven data services and future AI capabilities.

The pipelines, models and governance patterns you build won’t sit in the background. They will directly influence how data is trusted, shared and turned into value for customers and internal teams.

Start by building something customers will use

• Your first focus will be helping to deliver an initial customer-facing analytics data product on the new platform, while establishing reusable engineering patterns for future products

• Build AWS lakehouse pipelines using services such as S3, Glue, Athena, Lake Formation, DMS and Step Function

• Transform operational data into governed, reusable products for dashboards, APIs and customer-facing analytic

• Build in data quality, lineage, metadata and access controls from the star

• Work with architecture, platform engineering and analytics teams to create delivery patterns that can scale across the wider product portfolio

Build, shape and scale a modern AWS data platform

• You’ll be part of the team turning platform strategy into working, production-ready data capabilities

• Design, build and optimise cloud-native data pipelines, lakehouse structures and reusable data products on AW

• Ingest and transform data from operational systems using batch, CDC, event, file and API pattern

• Use lakehouse and medallion architecture concepts to move data from raw ingestion through to curated, business-ready product

• Create resilient transformations, quality checks and orchestration patterns that support reliable customer-facing analytic

• Embed governance by design, including metadata, lineage, data contracts, access controls and tenant-aware data handlin

• Collaborate closely with architecture, platform engineering, product and analytics teams to deliver scalable data solution

• Support product-level observability, performance optimisation, cost awareness and operational reliability

What We’re Looking For

Bring the skills to turn data into trusted products

• We’re looking for someone who can combine strong engineering delivery with curiosity, ownership and a practical understanding of how data becomes trusted business value

• Hands-on experience designing and delivering data engineering solutions on AW

• Strong SQL, dbt and Python skills, with experience building scalable pipelines, transformations and reusable dataset

• Good understanding of lakehouse architecture, medallion patterns, data modelling, data quality and data governanc

• A collaborative, ownership-led mindset and the confidence to work with engineering, product, architecture and business stakeholder

• Experience with analytics, BI, API or AI-ready data products would be highly valuabl

• Familiarity with data contracts, metadata, lineage, product ownership or Data Mesh concepts would help you succeed

Why Microlise?

When your groceries arrive at your door or you sign for your online parcel, one or more of our software, telematics or proof-of-purchase solutions has probably been used. Our solutions deliver value to many of the UK’s leading grocery retailers and food logistics providers as well as to household names including JCB, Eddie Stobart, Carlsberg, Waitrose, and Royal Mail.

Proudly Midlands-based, Microlise has been operating for over thirty years, and recently became a Publicly Listed Company with shares trading on the London Stock Exchange. Our growing business is guided by our culture which drives the way we behave, the way we work, the way we connect with our customers, and the way we support and develop our people.

• We believe in developing our staff and support our employees with their professional development goals

• 37.5 hour week with flexible working opportunities

• Great Place to Work certified – We have been recognised by the global authority on workplace culture, so come be a part of our success!

• Private medical insurance with Vitality Health including rewards for members such as: Apple Watch, discounted gym membership and many more!

• 25 days holiday, excluding bank holidays, increasing with service

• Invested in employee health and well-being with over 20 mental health first aiders in the business

• Employee Assistance Programmes

• Free Costco membership, 20% off EE mobile and line rental, and other discounts with Reward Gateway

• Great staff extras: Easter eggs, yearly BBQ, Christmas gifts and annual staff awards

Recruitment Process

For successful candidates, interviews will take place whilst the advert is still live, via telephone and video conferencing; so don’t delay getting your application in!

As part of the Microlise interview process, you’ll need to attend an in-person interview at our Head Office in Eastwood, Nottingham, for at least one of the interview stages