Top Data Jobs in Bristol

Lead discovery, design and delivery of data modernisation and migration projects. Design data lakes/warehouses/lakehouses and landing zones, advise on data strategy, governance and quality, implement Microsoft/Azure and Databricks platforms, support AI/ML initiatives, run workshops, produce technical documentation, contribute reusable assets, and support pre-sales and practice development.

Own and operate Databricks production data pipelines for a predictive CRM platform: monitoring, incident response, cost and performance optimization, migrating legacy ETL, onboarding customers, enforcing Delta Lake architecture and multi-tenant isolation, and applying CI/CD, security, and observability best practices to ensure reliable, scalable data delivery.

Design, build, and scale cloud-native data warehouses and robust ETL/ELT pipelines (primarily BigQuery). Optimize performance, implement partitioning and cost controls, ensure data governance, observability, and regulatory reporting support, and collaborate with analytics and engineering stakeholders.

Own analytics across the participant lifecycle to support acquisition, onboarding, activation, engagement, quality, retention and reactivation. Build metrics, dashboards, and experimentation frameworks with SQL and Python; partner with Product, Operations, Growth, and Data Science to run experiments and translate marketplace data into actionable decisions that improve participant health and supply sustainability.

Perform data extraction, entry, validation and quality checks across STW and Sapphire BigChange during system integration. Maintain records, liaise with field operatives and stakeholders, support customers, and assist IT/operations with automation and process improvement initiatives to ensure accurate, up-to-date data.

The role involves developing data pipelines, managing metadata and data quality in Azure, ensuring compliance with data governance standards, and collaborating with data teams.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

The Market Data Analyst will oversee data quality and operations for metals and minerals, monitor market trends, support clients, and improve data workflows using SQL and Python.

The role involves developing go-to-market strategies for VAST Data within the UK Defence & Secure Government sectors, building relationships with key stakeholders, identifying and closing strategic sales opportunities, and representing the company at industry events.

Senior Data Scientist owning end-to-end analytical problems: experiment design, predictive and inferential modeling, performance measurement, and cross-functional partnership to improve retail AI products. Duties include data acquisition, modeling, validation, auditing system outputs, building reusable statistical methods, and communicating findings to influence product and operations.

Lead end-to-end development and productionisation of time-series forecasting ML solutions: design, train, deploy models, build cloud-native data pipelines, collaborate with stakeholders, and monitor model performance to optimise clinic scheduling and staffing.

Lead end-to-end SAP S/4HANA data migration activities: define strategy and governance, manage mapping, cleansing, ETL and reconciliation, execute mock and production loads, resolve defects, coordinate with testing and business teams, and support cutover readiness.

As a Customer Data Solution Architect, you will design secure and scalable customer data solutions, providing thought leadership and ensuring compliance with design principles while collaborating across teams to enhance data strategies and analytics capabilities.

Lead UK sales strategy for data center customers, develop strategic relationships with hyperscalers and colocation providers, manage pipeline and forecasting, coordinate cross-functional pursuit teams, and drive profitable growth through customer engagement, specification, negotiation and long-term account development.

Lead design and governance of customer data solutions for retail: identity resolution, MDM, integration, and modern data platforms (lakes/lakehouses). Create design artefacts, enforce design principles, review solutions for compliance, collaborate with stakeholders, and apply industry trends to improve personalization and analytics.

Build and maintain production data pipelines and features in Python; own project lifecycle from design to reliable production; set technical direction for the Insights platform; improve engineering standards (testing, observability, data quality); apply AI across products and pipelines; help establish semantic/AI-ready data layers.

The Senior Product & Growth Data Scientist will analyze user behavior, run experiments, shape product strategy, and influence growth metrics to drive company success.

As a Data Scientist, you'll empower the company with data insights, develop metrics and experiments, and collaborate with various teams to drive product decisions.

The Senior Data Engineer will design and maintain scalable data pipelines, ensure data quality, and develop backend services to support WalletConnect's payments infrastructure and analytics.

Lead design and delivery of scalable analytics, BI, forecasting, and AI-driven solutions for RevOps Sales Intelligence. Partner cross-functionally to improve data quality, governance, automation, and self-service analytics using cloud data platforms and modern ML/Generative AI techniques. Manage roadmap, stakeholder communication, and operationalize AI/analytics at enterprise scale.

Lead high-complexity analytics projects: partner with stakeholders, prepare and blend large datasets, apply intermediate statistics, build models and visualizations, deliver insights, and mentor junior analysts.

Design and implement core YTsaurus functionality in C++, build and evolve platform-level capabilities, improve APIs and UX for internal users, own production quality including incident response/on-call, and collaborate with stakeholders to prioritize and deliver scalable data platform features.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

The Data Standards Lead will develop and govern data standards for licensing, ensure data interoperability, and guide teams in applying these standards.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.