Top Data Jobs in Edinburgh

The role involves managing data implementation projects, client engagement, requirements collection, and technical analysis for investment data solutions at BlackRock.

Analyze products to provide strategic recommendations, design experiments for product improvements, and maintain data infrastructure for analyses.

As a Sr. Data Engineer, you'll lead data ingestion, processing, and management in Azure Databricks, collaborating with stakeholders and designing efficient data workflows.

Lead AI/ML research initiatives in cybersecurity, develop novel machine learning models, analyze datasets, and translate research into deployable solutions.

As an Associate, you will manage data quality initiatives, collaborate with stakeholders, perform data analysis, and assist in implementing data ownership programs within CIB Markets.

The Senior Director Analyst delivers insights to government IT executives, focuses on research and advisory roles, and improves technology use in government modernization.

The Staff Data Engineer will lead the design and implementation of critical data infrastructure, collaborating with teams to build scalable, efficient systems and improve data quality and observable practices.

The role involves leading Subsurface analytics, fostering relationships with clients, and delivering AI-driven solutions in the energy sector.

The Senior Data Engineer will develop a centralized data model for reporting and insights, improving data quality, and mentoring junior team members.

The Data Owner manages enterprise master datasets, collaborates with teams on data structure, designs data models, and ensures data quality and utility.

The Head of Data will develop and execute data strategies, lead data teams, and ensure data governance and analytics initiatives are aligned with business growth.

The Data Scientist II will analyze datasets to optimize underwriting processes, improve cyber risk selection, and support strategic decisions through data-driven insights and collaboration with cross-functional teams.

The Associate Data Engineer will support the data team with tasks like automating processes, data extraction, and pipeline setup, primarily using Python. They will collaborate on requirements, design solutions, and document processes.

Develop and deploy machine learning models for claims automation. Lead projects, mentor juniors, and influence AI strategy while collaborating with product teams.

Analyze product performance, provide insights, collaborate with product teams, develop data models, and create dashboards to inform product strategy.

The Lead Data Architect drives the enterprise data architecture, aligning it with business goals, optimizing data integration, and leading teams through innovative data strategies.

The Analyst creates impactful Gartner research on AI and ML, advising clients and supporting sales teams through analysis and presentations.

The Lead Data Architect will shape data strategy, mentor teams, and design secure data architectures on AWS for high-profile projects.

The Data Analyst will manage and analyze large datasets to enhance forecasting and modelling efforts, focusing on automating workflows and ensuring data quality while collaborating with various teams.

The Senior Product Data Analyst will transform raw data into insights, build data workflows, and evaluate product metrics to drive strategic decisions.

Lead the design and delivery of ETL/ELT pipelines, focusing on data quality, and drive technical leadership in data engineering. Collaborate with teams to align data solutions with business needs and oversee the optimization of AWS data infrastructure.

As a Data Engineer, you will design and maintain data systems, develop complex Spark jobs, and collaborate with technical teams to optimize data processing and drive engineering excellence.

The Business Analyst (Data Steward) manages data quality and governance for transportation datasets, collaborating with stakeholders to ensure effective data usage and compliance.

The Senior Data Engineer will manage the data platform, support product development, and handle complex data systems. Key skills include Python, SQL, and cloud infrastructure management.

Lead design and development of data architecture and pipelines using Snowflake. Ensure data quality and mentor junior engineers while optimizing data flow and performance.