7 of 7 Contract Data Modelling Jobs in Manchester

Cloud Data Engineer (Python) Up to £54,150 per annum + excellent pension | Hybrid working | London, Manchester, Cardiff, Belfast, Edinburgh or Darlington Are you an experienced Data or Software Engineer with hands-on experience of: Python and end to end Cloud deployment, looking for a role where your … work can make a real difference? Our Government client is looking for a Data Engineer to join its Data, Technology and Insights (DTI) unit on a 12-month fixed-term contract . Youll join a multidisciplinary team of data engineers, data scientists, technologists, behavioural scientists ...

Data Engineer - Enterprise Knowledge & AI Platform 1 Vacancy | Leeds, Manchester or Edinburgh | Hybrid - 2 Days on Site Contract: Initial term to 20 December 2026, with a view to extend | multi-year programme We're looking for a Data Engineer to join a major UK financial services organisation embarking … exciting technology transformation. You'll be part of a multi-year programme building a new enterprise knowledge platform from scratch, transforming data and knowledge from across the organisation into trusted, searchable and AI-ready assets. This is a genuine greenfield opportunity where you'll help build the data ...

Data Manager | BigQuery | Data Governance | ETL | SQL | 3-4 Month Contract | £600-£650 per day | Outside IR35 | Manchester We're working with a well known client based in Manchester looking for a Data Manager to support their data function on an initial 3-4 month contract. … hands-on role focused on maintaining and improving a BigQuery environment. What you'll be doing: Owning and maintaining the BigQuery platform Managing data pipelines and resolving issues Supporting data governance and data quality initiatives Enhancing data models and warehouse structures Working closely with analysts ...

with Micro-Frontend (MFE) architectures (e.g., Module Federation). Backend: Java & Spring Boot (building/consuming RESTful APIs & BFF layers). Solid understanding of data modeling ( SQL or NoSQL ). Cloud & DevOps: Proficiency with AWS services (ECS/EKS, CloudFront, API Gateway, Lambda). Infrastructure-as-Code (CloudFormation ...

office Role Overview We are looking for a Lead Technical Product Manager to own and scale our core API platforms, backend microservices, and data tools. You will lead cross-functional engineering teams to build high-performance systems, improve developer experience, and integrate AI/data solutions across … Strategy: Own the roadmap and backlog for core APIs and microservices, ensuring high availability, speed, and scalability. Technical & AI Execution: Work with engineers and data teams to design data models, APIs (REST/OpenAPI), recommendation engines, and AI workflows. Data Governance: Build clear data policies ...

Infrastructure: Hands-on skill with AWS services and deployment mechanisms like CloudFormation. Databases: Core understanding of relational (SQL) or non-relational (NoSQL) databases and data modeling principles. Testing & Quality: Ability to write unit and integration test suites to maintain software reliability. Version Control & Tools: Experience working with … scalability, fault tolerance, and monitoring metrics (SLIs/SLOs). Domain Knowledge: Background or strong interest in user engagement, recommendation systems, or notification architectures. Data-Driven Practices: Understanding of data analytics and A/B testing within product development workflows. Scale: Prior experience engineering applications that serve large ...

into our platform. You'll focus on building resilient, cloud-native services that manage product ingestion, availability streams, real-time messaging, webhooks, and complex data translations-ensuring seamless communication between external platforms and internal microservices. Responsibilities Architect, deploy, and manage distributed backend microservices powering critical third-party integrations. Create … reliable, event-driven data flows to process partner product updates, availability matrices, and transactional notifications. Apply strong distributed systems practices (fault tolerance, retries, rate-limiting, and idempotency) while leveraging metrics and tracing to maintain system health. Own the Lifecycle: Take end-to-end technical ownership-from refining specs ...