Arbetsbeskrivning

What makes Cognizant a unique place to work? The combination of rapid growth and an international and innovative environment! This is creating lot of opportunities for people like YOU — people with an entrepreneurial spirit who want to make a difference in this world.

Cognizant's delivery model infused with a distinct culture of high customer happiness. We consistently deliver positive relationships, cost reductions and business results. Are you ready to be a change-maker?

About the Role

Our Client is seeking a seasoned Senior Data Engineer & Architect to lead the design and evolution of their data landscape within the Industrial Operations Hub. You will build a scalable, AI-ready foundation that powers the next generation of industrial intelligence — setting standards, shaping culture, and partnering across the organisation to make data a true strategic asset.

This role is situated in Göteborg, Sweden.

Key Responsibilities

Architect and design end-to-end data solutions aligned with Volvo Cars' analytics and AI strategy, using the core tech stack: Azure, dbt, Snowflake, and Redpanda.

Define data and integration standards for building robust, reusable data products that are AI-ready by design.

Build AI-first data pipelines and applications leveraging Snowflake Cortex, Copilot, and semantic modelling.

Champion and spearhead an AI-native way of working across all engineering development cycles.

Liaise between the Industrial Operations Hub and Core Data, spoke, business, and digital teams to federate AI initiatives and bridge AI needs with org-mandated platforms.

Define best practices for data modelling, data contracts, metadata management, and data quality.

Mentor engineering teams on modern architecture patterns and AI-native development approaches.

What You Bring

10+ years of experience in data engineering and architecture in complex enterprise environments.

Deep expertise in Azure, Snowflake (including Cortex, Snowpark), dbt, and streaming/event-driven architectures (Redpanda, Kafka or equivalent).

Experience building data products within a Data Mesh or domain-oriented architecture.

Hands-on familiarity with semantic modelling, AI/ML pipelines, and GenAI/LLM integration patterns.

Strong communicator able to engage both technical teams and business stakeholders.

Ability to lead by influence, drive standards, and thrive in a federated, multi-team environment.

Nice to Have

Background in automotive, manufacturing, or industrial operations.

Knowledge of DataOps/MLOps practices, data contracts, or Microsoft Fabric/Databricks.