Top Data Jobs in Edinburgh

This role involves owning the EMEA pipeline, executing GTM plans, driving conversion, and improving lead quality across various channels and markets.

Take end-to-end ownership of backend features and SaaS services in a microservices architecture. Design, implement, deploy, and operate scalable, reliable Node.js services. Work with Redis Streams, MongoDB, Kubernetes, and ensure test coverage, performance tuning, and collaboration with cross-functional teams.

Hands-on role ensuring completeness, quality, and accuracy of product data for multi-region launches. Perform data validation, stewardship, QA, syndication (PIM), reporting, and stakeholder coordination to resolve discrepancies and track launch readiness.

Design, build, test and document secure batch and real-time data pipelines, perform logical/physical database design and data modelling, expand platform capabilities, analyse and resolve data processing issues, and ensure alignment with data architecture for downstream consumers.

Build, test, and document secure batch and real-time data pipelines for a government client; design logical and physical databases; extend platform capabilities; ensure data models align with architecture; perform data analysis and root-cause investigations to improve processing and availability for downstream consumers.

Lead electrical design and technical delivery for hyperscale and mission‑critical data centre projects across feasibility to handover. Define power architectures, perform power systems and protection studies (ETAP/SKM), integrate BMS/EPMS/SCADA and metering, embed decarbonization and energy efficiency measures, ensure compliance with standards, and coordinate multidisciplinary interfaces while mentoring teams and supporting business development.

Build and own pricing data science capabilities, including demand and elasticity models, forecasting, willingness-to-pay models, pricing optimization, experimentation, and causal analysis. Deploy and monitor machine learning systems, establish governed pricing metrics, and partner with Commercial, Finance, and Product to improve margin and revenue. Set analytical standards for pricing decisions and build reusable analytical capabilities.

Designs and governs enterprise data architectures supporting analytics, reporting, operations, and AI initiatives. Responsibilities include data modeling, warehousing, integration pipelines, APIs, governance, quality, lineage, security, and architecture optimization. The role provides technical leadership and mentorship, guides cloud and big data technology decisions, develops proofs of concept and roadmaps, and supports client proposals and account growth. Collaboration with engineers, analysts, developers, and business stakeholders is central to delivering scalable, secure, high-performance data platforms.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Provides senior consulting expertise on data strategy, architecture, governance, transformation roadmaps, and scalable Microsoft Fabric solutions. Partners with clients, leads workshops, translates business needs into technical designs, supports pre-sales activities, develops proofs of concept, and contributes to proposals. Acts as a Microsoft Fabric subject matter expert while mentoring consultants and developers and managing multiple delivery priorities.

Leads data engineering teams building scalable, governed data products and platforms. Responsibilities include overseeing architecture, ingestion pipelines, orchestration, governance, security, access control, performance optimization, and Bronze/Silver/Gold data layers. The role manages delivery of analytics-ready datasets at very large scale, coaches engineers, and partners with analytics, business, and customer stakeholders to produce actionable operational and financial insights.

Support development and continuous improvement of data products for electricity transmission network planning and operations. Define roadmaps, manage backlogs, gather requirements, validate data quality and lineage, collaborate with stakeholders and delivery teams, enable analytics and governance, and measure product performance and adoption.

Lead business discovery and requirements analysis for data, reporting and analytics initiatives. Define processes, KPIs, data models, lineage and governance. Collaborate with analytics, data architects and delivery teams to elicit, validate and prioritise requirements, support testing, adoption and continuous improvement while managing stakeholders and multiple concurrent initiatives.

Lead enterprise data governance by defining frameworks, policies, and operating models. Manage data quality, metadata, catalogs, lineage, stewardship, compliance, and MDM. Collaborate with stakeholders, run governance councils, track KPIs, and support analytics, cloud, and AI initiatives.

Develop stored procedures or notebooks to build 230 additional data items into DCoE tables/views. Create an extensible, config-driven process to add fields with minimal re-engineering. Produce self-documenting, well-commented code and collaborate with the DCoE team on delivery; DCoE handles business analysis, design sign-offs, data modeling, and testing.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

The Senior Data Engineer will enhance backend systems for a social media app by managing databases, optimizing recommendation algorithms, and ensuring accurate recommendations.

Design and evolve a scalable, multi-tenant cloud data platform prioritizing stability, fault tolerance, cost efficiency, developer productivity, and security-by-design. Define architecture standards, review designs, modernize legacy components incrementally, implement monitoring and observability, prototype new technologies, and provide technical guidance so teams can ship reliably and quickly.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.

As a Data Architect, you'll lead traditional data architecture practices, provide technical guidance, manage a team, and engage with clients.

Define and build quality frameworks for human data programs, partner with clients and engineering to design evaluation, recruitment and annotation strategies, implement automated checks and dashboards, investigate data integrity, and upskill teams to deliver high-quality human data at scale.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Lead multi-skilled agile teams to design, build and productionise modern data solutions. Own technical architecture, collaborate with infrastructure and customer architects, define functional and non-functional designs, mentor staff, estimate delivery timelines, contribute to data community and support pre-sales technical solutioning.