1 day ago
Bristol, United KingdomEntry Level
Responsibilities
- Build and operate cloud data and platform solutions across Azure, AWS, GCP, Databricks, Microsoft Fabric, and Snowflake.
- Develop and maintain scalable batch and streaming data pipelines using ETL/ELT patterns.
- Build cloud infrastructure with Infrastructure as Code tools and contribute to automated environment provisioning.
- Implement CI/CD pipelines for data and platform solutions using Git, Azure DevOps, or GitHub Actions.
- Apply dimensional and Kimball modelling, medallion architecture, and source-to-target mapping.
- Implement data quality, lineage, observability, monitoring, networking, identity, access management, and security controls.
- Use GenAI and AI-assisted development tools to accelerate engineering, testing, and documentation.
- Develop understanding of agentic AI systems and design data and platform foundations suitable for agentic consumption.
- Collaborate with architects, product engineers, and business stakeholders on technical and business requirements.
Requirements
- Experience with cloud engineering across one or more of Azure, AWS, GCP, Databricks, Microsoft Fabric, or Snowflake.
- Python and SQL experience with strong engineering fundamentals.
- Experience developing batch or streaming pipelines, cloud infrastructure, platform engineering, or a combination of these areas.
- Experience with CI/CD tooling for data and platform delivery, including Git, Azure DevOps, or GitHub Actions.
- Practical experience using GenAI or AI-assisted development tools such as GitHub Copilot, Cursor, or Databricks Assistant.
- Awareness of how data quality, latency, schema, security, and lineage affect downstream AI and ML systems.
- Basic understanding of agentic AI concepts and autonomous systems’ dependencies on data and platform infrastructure.
- Data modelling, agentic workflow, LLM application, data product, Infrastructure as Code, cloud networking, identity, access management, security engineering, policy-as-code, or platform governance experience is advantageous.
- Relevant cloud, data platform, AI, or ML certifications are advantageous, including Azure Data Engineer Associate, AWS Data Analytics Specialty, Databricks Certified Associate Developer, AWS Solutions Architect Associate, Databricks Generative AI Engineer, AWS Machine Learning Specialty, or Google Professional ML Engineer.
Benefits
- 25 days’ vacation per year.
- Private medical insurance.
- Three additional days of leave per year for charitable work.
- Flexible and mobile working is required, including time onsite with clients and partners.
- Bristol location; application closing date is 18/12/2026.
Categories
Data EngineeringDevOps
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.