Top Data Jobs in Bristol

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 insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

Build and operate distributed ingestion and processing pipelines, ensure reliability and performance, define data contracts, add observability and testing, improve platform reliability and CI/CD, and participate in design/code reviews and incident retrospectives.

The Product Manager for Data will lead the rollout of data products for clients, overseeing requirements, development support, adoption, and communication while contributing to a global data model.

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.

Maintain and create supply chain and intercompany master data in SAP and related systems for EMEA. Ensure data quality, compliance with SOPs, support product launches, troubleshoot system issues, drive process improvements (MDM/Winshuttle), and contribute to global master data initiatives while supporting costing and training materials.

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.

The role involves leading data engineering projects in the public sector, creating technical designs, implementing solutions, and managing teams to drive technical outcomes for customers.

Lead and manage clinical data management for studies from database design and set-up through cleaning, validation and database lock. Coordinate with cross-functional teams and external vendors, develop DM plans and standards (CDISC/CDASH), oversee UAT, data transfers/reconciliation, metrics reporting, quality reviews, audits, training and mentoring, and contribute to process and tool improvements and client interactions.

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 role involves designing and implementing Master Data Management solutions, assessing enterprise data domains, and defining governance structures, requiring strong consulting skills and Azure expertise.

Lead mechanical delivery for hyperscale and co-location data centre projects across UK/EMEA. Drive technical excellence, client relationships, work winning, project financials, team leadership, and represent AECOM in the data centre community.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.