Top Data Jobs in Edinburgh

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.

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.

Design, build, and maintain scalable data pipelines and platform services to support analytics, ML, and product teams. Implement infrastructure-as-code (Terraform) and Kubernetes-based deployments, develop data services/APIs, and ensure data quality, observability, security, and compliance. Partner with cross-functional teams, document systems, and continuously improve performance and reliability.

Lead development of data centre sustainability measurement and certification. Conduct discovery with operators and buyers, stress-test verification approaches, translate technical rigor into assessments and reports, and help win initial customers.

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.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

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.

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.

Support development, execution and optimisation of multi-channel media campaigns (AV, social, digital, OOH). Coordinate with agencies and stakeholders, monitor performance against KPIs, prepare reports/dashboards, manage budgets, implement testing and learning, and recommend optimisations to improve media effectiveness and ROMI.

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

Manage a multifunctional clinical operations/data review team in an FSP environment, ensuring quality deliverables, KPI compliance, customer issue escalation, resource planning, revenue impact, and people leadership including performance management, training, workload oversight, and staff development.

Build production AI-powered tools, data pipelines, and internal full-stack applications that automate incident investigation, surface anomalies, and enable AI agents to interact safely with platform systems. Work across Python, TypeScript, Go and SQL, deploy on Docker/Kubernetes/AWS, and collaborate with TechOps, Connectivity, and Data teams to own, monitor, and improve shipped systems.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

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

As a Commercial Account Executive, you'll engage customers, manage sales opportunities, create pipelines, forecast business, and communicate with various teams to close sales successfully.

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.

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

Lead end-to-end SAP data migration for large S/4HANA programs: analyze legacy and target models, define mappings, perform profiling and cleansing, build migration datasets with SAP tools, develop reusable frameworks and automation, create data quality dashboards, support cutover and post-go-live stabilization, and mentor data teams.

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

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.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Lead pre-sales technical engagements for a data management/DSPM platform: perform technical discovery, architect solutions, run demos and POCs, enable partners, support RFPs, and liaise with product, marketing, and customer success to drive enterprise sales and adoption.