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
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