Stockholm, Sweden

Job Description

Scandic is the leading hotel company in the Nordics, committed to creating great experiences for the many people. With a strong financial foundation and bold ambitions for the future, we are investing in technology, and people.

About the role

As Manager / Tech Lead Data Analytics, you will lead Scandic Tech's Analytics unit. This is a key role in how we build, develop and use data and analytics across the company. You will manage a team of data engineers and BI developers, with full responsibility for people, delivery and ways of working. The role is a lot about leadership. You'll create clarity, structure and focus for the team, while at the same time acting as a strong partner to the business. You will work in an environment with many parallel initiatives and stakeholders at different levels of the organization.

You will report to our Head of Tech for Analytics, Finance & Team Member Journey and play an important role in shaping how Scandic works with data, insights and data analytics going forward.

Tech-wise: Cloud-based data platform hosted on Microsoft Azure. Snowflake as the data warehouse. dbt used for data transformations. Snowpipe used for data ingestion. Power BI used for visualization and self-service reporting.

Your focus will be to:

• Lead and manage the Data Analytics team, including employees and consultants, with full people responsibility.
• Plan, prioritize and manage the tech analytics backlog in an environment with many parallel initiatives.
• Work with requirements from stakeholders across the organization and translate them into development-ready work. Assess technical complexity in incoming initiatives and support prioritization decisions.
• Take overall responsibility for Scandic’s data and analytics platform and architectural direction, in close collaboration with our architects.
• Contribute to the ongoing modernization of the analytics platform, including the transition from Matillion to dbt.
• Support the organization in working with data and analytics, including helping stakeholders understand how insights can be used.
• Support the establishment of analytics domains, including customer and loyalty data.