Data & AI Engineer

Overview In this Data & AI Engineer role, you contribute to building cloud data and AI-ready platforms for enterprise clients. You will work across the Data & AI practice, applying AI-assisted approaches to design, build and test data pipelines and platform foundations.

The role emphasizes collaboration with architects, engineers and stakeholders to deliver scalable data solutions and enable agentic AI consumption. You will learn and grow in a culture that values innovation, inclusion and boundaryless opportunities.

This position offers hands-on work with leading cloud and AI tooling in a global network. Pay / Benefits competitive salary private medical insurance 25 days vacation 3 extra days for charitable work flexibility and mobility to work onsite with clients Responsibilities Build and operate cloud data and platform solutions on Azure, AWS, GCP, Databricks, Microsoft Fabric, Snowflake Develop and maintain scalable batch and streaming data pipelines using ETL/ELT patterns Create and manage cloud infrastructure with IaC (Terraform, Bicep, CloudFormation) Implement CI/CD pipelines for data/platform delivery using Git, Azure DevOps, GitHub Actions Apply data modelling (dimensional/Kimball, medallion architecture) with AI tooling for model iteration Establish data quality, lineage, observability and monitoring with automation and AI-assisted tooling Support cloud platform operations including networking, IAM, security and policy adherence Leverage GenAI and AI-assisted tools to accelerate development, testing and documentation Develop understanding of agentic AI concepts to inform design of data and platform solutions Collaborate with architects, product engineers and business stakeholders to align technical solutions with business needs Key requirements Cloud engineering experience across one or more: Azure, AWS, GCP, Databricks, Microsoft Fabric or Snowflake Python and SQL Experience with batch and/or streaming pipelines or cloud infra/platform engineering CI/CD tooling for data/platform delivery (Git, Azure DevOps, GitHub Actions) Practical use of GenAI/AI-assisted development tools in daily work Familiarity with AI-ready architecture concepts (quality, latency, security, lineage) Basic understanding of agentic AI concepts and interactions between autonomous systems and data/platforms Curious and driven technologists Collaborative and cross-functional teamwork Ability to learn quickly and apply new tools Azure, AWS, GCP, Databricks, Microsoft Fabric, Snowflake Python SQL

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