Top Data Jobs in Edinburgh

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.

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.

Abstract and enter clinical data from health records, ensure data quality and confidentiality, use EHR/practice management systems and Microsoft Office, troubleshoot basic access/VPN/MFA issues, and collaborate with clinical teams to support operations.

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 design and delivery of a deterministic identity graph and graph-driven identity intelligence. Discover features from connected data, build link-analysis pipelines, prototype identity-resolution and fraud/risk models, define quality signals and ingestion workflows, align data capabilities with product goals, select graph technologies, document standards, and mentor/grow a data science team while shipping production-grade graph-enabled product features.

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.

Design and deliver scalable Customer Data Platform solutions (Oracle Unity), build and operate data pipelines and Customer 360 models, integrate CDP with data lake/CRM/marketing systems, lead architecture and data modelling workshops, ensure data quality, governance, security, and support CDP operations, and partner with Oracle implementation teams.

Work with stakeholders, product and technical teams to elicit, document, and translate business and data requirements into user stories and acceptance criteria. Support backlog refinement, run workshops, assist data analysis and validation, and identify process improvements to enable data-driven decisions.

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.

The Solution Architect will design and implement big data solutions for overseas clients, requiring expertise in various big data technologies and cloud services, as well as strong communication and technical presentation skills.