Arbetsbeskrivning

Scandinavian Airlines System SAS

At SAS, data is the engine behind everything we build from AI models and personalized offers to real-time operational intelligence. As Lead Data Engineer, you will strengthen the engineering foundation that makes all of it possible: reliable, scalable, well-operated data products, pipelines, and integrations. You will work closely with the Data Architect to turn architectural direction into practical engineering standards, modern DataOps practices, and production-ready solutions that create real business impact.

We are looking for a Lead Data Engineer who will act as a senior engineering leader and close partner to the Data Architect, driving the development of scalable and reliable data solutions across SAS. You will lead the implementation of engineering standards for data testing, observability, monitoring, , SLAs, version control, and DataOps practices, while supporting teams in adopting modern software engineering practices.

You will work at the technical frontier of our data stack, leading implementation choices, code reviews, technical standards, and engineering quality across data products, pipelines, and integrations. In close collaboration with the Data Architect, Data Scientists, ML Engineers, and business stakeholders, you will bring modern perspectives on data products, DataOps, and software engineering craft, while ensuring solutions are aligned with the broader enterprise architecture and stakeholder priorities.

As Lead Data Engineer you will bring deep engineering expertise and hands-on DataOps leadership, helping transform architectural intent into robust, maintainable, and production-ready solutions.

Your responsibilities include:

• Lead the design, development, and operation of scalable data pipelines, data products, and integrations.
• Establish and drive engineering standards for testing, documentation, observability, monitoring, , SLAs, version control, and DataOps.
• Partner with the Data Architect to translate architectural direction into practical implementation patterns and reusable engineering standards.
• Lead code reviews and drive continuous improvement of engineering practices across the team.
• Mentor and support data engineers and DataOps engineers in modern tools, standards, and software engineering practices.
• Collaborate with architecture, data stewardship, IT, cloud teams, and business stakeholders to ensure solutions meet quality, security, governance and operational requirements.

The Analytics & Data team develops and manages the data infrastructure that powers AI, analytics, and business operations at SAS. We build and maintain data pipelines, data products, and enterprise integrations on a modern cloud platform.

Working closely with the AI & Automation team, analysts, and business units across SAS we ensure that trusted and accessible data is available where it is needed. Our work spans batch and near-real-time pipelines, data product development, and integration with core operational systems.

As SAS continues to expand its AI and analytics capabilities — including a new Customer Data Platform, agentic AI pilots, and an expanding BI estate — the demand for high-quality and well-engineered data infrastructure continues to grow. We are looking for a lead who can drive this forward.

• A degree in computer science, engineering, or a related field.
• At least 5 years of hands-on data engineering experience, including experience in a senior or lead role.
• Strong skills in SQL and Python, with experience in Spark or similar distributed processing frameworks.
• Experience building and operating cloud-based data pipelines, preferably in Azure using services such as Azure Data Factory, Azure Databricks, Synapse, or equivalent.
• Solid understanding of data modelling, data warehouse design, data lake architecture, and enterprise data solutions.
• Practical experience with DataOps, version control, CI/CD, automated testing, monitoring, alerting, and operational SLAs.
• Experience with orchestration and transformation tools such as Azure Data Factory, Airflow, Prefect, Lakeflow, or dbt.
• Strong mentoring skills and an passion for helping others grow through clear standards, documentation, and practical guidance.
• A collaborative mindset, strong communication skills, and the ability to bring practical engineering perspectives into architectural discussions.

• Apply by: 11/09/2026. We review applications continuously, so please send us your CV as soon as you can. The role may be filled before the deadline.
• Start and scope: Full-time role, starting with a 6-month probation period.
• Location: You’ll be based at our office in Frösundavik, Solna, Stockholm. This is mainly an onsite role, with some flexibility for remote work depending on the agreement with your manager.
• Security: As this role is security classified, a background check will be part of the final stage of the recruitment process.

If you have any questions about the role, please contact Jonas Blomqvist, Head of Analytics & Data, at [email protected]. Please note that, due to GDPR, we can’t accept applications by email.