Top Data Jobs in Edinburgh

Design, build, and maintain scalable cloud-based data platform and ETL pipelines on Azure. Develop data models, ensure data quality, optimize performance, implement governance and security, and collaborate with stakeholders and data scientists to enable data-driven solutions.

Lead design and implementation of data governance and MDM strategies, develop policies and metadata/lineage practices, enforce data quality, deploy governance tooling, engage stakeholders, ensure regulatory compliance, and mentor team members.

Define, set up and ingest external clinical data streams (labs, ECG, imaging, EHR, wearables, genomics). Plan set-up activities, create trial-specific Data Transfer Agreements, translate medical concepts into data mappings, perform UAT, implement transfers into the CDR, monitor data quality and resolve provider conformance issues while ensuring regulatory and data protection compliance.

As a Senior Data Scientist, you'll develop AI solutions with machine learning, mentor others, and ensure responsible AI practices while collaborating with clients to solve business challenges.

As a Lead Data Engineer, you will design and develop software for data processing, lead a team, ensure quality, and manage technical proposals.

As a Data Architect at Kainos, you will provide guidance on data architecture, manage a small team, ensure data solutions fit client needs, and engage with stakeholders. You will also lead technical projects and support junior staff development.

Design, build, and maintain high-volume distributed data processing jobs and pipelines (Redshift, Athena, Iceberg, Spark, Airflow). Collaborate with data scientists and analysts to productionize models, optimize performance, troubleshoot systems, and mentor junior engineers. Support lakehouse/data warehouse management and ensure data accuracy and efficiency.

Lead a small senior data engineering team owning the end-to-end data platform: streaming, warehousing, modelling, pipelines, ML lift, and operational excellence. Drive delivery, coach engineers, review technical designs, enforce data contracts and quality, manage costs (FinOps), and partner with Product and leadership to set roadmaps and risk. Build and grow an emerging ML function.

Design, build, and maintain scalable batch and streaming data pipelines, internal tools, and APIs to support analytics, product features, and ML. Collaborate with product and engineering to improve data infrastructure, ensure reliability, testing, and observability in a cloud-native environment.

Lead high-value analytics projects: translate business questions into analysis plans, run exploratory and diagnostic analysis, apply statistical and quasi-experimental methods, evaluate initiatives, quantify impact, and coach analysts while shaping analytical standards across Marketing & Sales.

Lead analytical work to inform high-value decisions: translate business questions into analysis plans, run exploratory and diagnostic analysis, design statistical models, experiments and quasi-experimental methods to quantify impact, and coach analysts while shaping analytics standards and best practice.

Provide second-line oversight of technology, cyber and data risks. Assess risk assessments, test critical controls, challenge first-line teams, inform risk framework evolution, and deliver assurance to senior management to ensure resilient, secure digital services and data protection.

Partner with product and business teams to define metrics, design and analyze experiments, build analytical frameworks, maintain governed dashboards, conduct deep-dive analyses (funnels, retention, cohorts), size opportunities, and connect product metrics to revenue to inform roadmap and leadership decisions.

As a Data Scientist, you will design and deliver bespoke AI solutions, work with clients on project feasibility, and ensure delivery excellence while acting as a technical advisor.

This role involves analyzing complex datasets, developing metrics, building dashboards, and collaborating with teams to enhance fraud detection strategies using ML models.

Design and validate agentic AI capabilities for Protege in PatentSight using ML, NLP, and LLMs. Build retrieval and hybrid search strategies, run experiments, evaluate models, analyze large IP datasets, and translate results into product recommendations while collaborating with engineers, product, and IP experts.

Design, experiment, and validate NLP/LLM and generative AI solutions for patent intelligence. Develop agentic workflows, retrieval strategies (hybrid semantic+lexical), evaluation metrics, and large-scale text processing methods. Partner with product and engineering to translate validated models into scalable, customer-facing features and deliver measurable business impact.

The Data Engineer will build and scale data pipelines, ensure data quality, implement dbt best practices, and empower cross-functional teams with self-service data access.

Perform data profiling and validation across source and target systems during a large-scale public sector data migration. Define and execute data quality rules, test BI dashboards, write and run SQL (MySQL) including stored procedures, document findings, and collaborate with data engineers to remediate issues while championing data quality across accuracy, completeness, consistency, timeliness, validity, and uniqueness.

Lead client-facing data platform architecture and strategy. Design scalable Databricks/Azure or AWS-based solutions, oversee multi-team delivery, incident response, governance, and data security. Mentor engineers, drive roadmap and budget decisions, and ensure resilient, high-quality data pipelines aligned to business goals.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.

The Data Scientist (Product Analytics) will develop product analytics, improve data quality, conduct A/B tests, analyze user behavior, and collaborate with cross-functional teams to inform product strategies and enhance user engagement.

Lead a specialist BPA data team to manage end-to-end pension scheme data for buy-in/buy-out transitions. Ensure data accuracy, validation, reconciliations, benefit specification oversight, governance, regulatory compliance, stakeholder integration, third-party data management, and drive automation and continuous improvement to support successful scheme migrations.

Support implementation of data governance frameworks across Pensions & Savings. Work with Data Owners, Stewards, and Risk to monitor data quality, track governance actions, maintain documentation, and produce regular and ad-hoc reports to support regulatory compliance and governance maturity. Contribute to continuous improvement of data governance processes and stakeholder reporting.

Lead and scale Western Europe sales team to hit ARR targets through hiring, coaching, pipeline management, and executive deal support. Drive new business, retention and expansion, align with Product/Engineering/Compliance, and enable data-driven sales processes for complex data, API and cloud-based solutions.