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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AWS Data Engineer - **Company:** Microlise - **Location:** Eastwood, UK - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Business Analytics Applications, Data Analysis, Data as a Services, Data Architecture, Data Files, Software Design Patterns, Python (Programming Language), Machine Learning, Metadata, Operational Data Store, Performance Tuning, Standard Sql, AI Platforms, AWS Data Analytics, Operational Systems, Data Management, Api Design, Data Pipelines - **Published:** September 19, 2026 - **Apply:** https://www.totaljobs.com/job/senior-aws-engineer/microlise-job108005190 ## About the Role 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 ## Description 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 ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [API Design - Getting Started](https://www.wearedevelopers.com/videos/33-api-design-getting-started) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Hate organising your photos? 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