(Senior) Data Engineer (Snowflake) – Building and Technical Trade, K Group

Snowflake is becoming the foundation of Building and Technical Trade's future data ecosystem. As a (Senior) Data Engineer, you'll help define how data is modelled, built and utilized across analytics, AI and business development. Rather than joining a fully established environment, you'll have a rare opportunity to influence the development practices, data models and technical standards that will shape our future data platform. We are open to candidates from experienced Data Engineer to Senior Data Engineer level. The exact scope and level of responsibility can be shaped based on your background and expertise. You will work as part of Kesko's Central Data & Analytics Platforms team while collaborating closely with Building and Technical Trade's Data, AI and ESG team. Together with BI analysts, analytics engineers, data experts and business stakeholders, you'll turn business needs into scalable and reliable data solutions that support both daily decision-making and future growth. We are working in a hybrid workplace model where we combine office days at K Kampus in Kalasatama and remote work to best suit both the role and the team. Come and join our professional team and start building your own kind of career in K Group! What is the role about? As a (Senior) Data Engineer, you will be a key data expert helping BTT build a modern Snowflake-based data foundation for analytics, AI and business development. This is a hands-on senior role with strong architectural influence: you will help shape how Snowflake development is done in BTT, while working closely with the BTT Data, AI and ESG team and Kesko’s central data platform experts. In addition to building solutions, you will help grow the team’s Snowflake capabilities through collaboration, mentoring and practical examples. Your Key Responsibilities Include Technical ownership: owning the technical direction of BTT’s Snowflake solutions and ensuring that solutions are reliable, maintainable and aligned with agreed platform principles Best practices and architecture: defining BTT’s Snowflake development practices, including modelling approach, warehouse strategy, documentation, quality and maintainability, while contributing to the broader data architecture and innovation Mentoring and collaborating: coaching BTT data team members towards stronger Snowflake competence, collaborating with BI analysts, analytics engineers and business stakeholders, and translating business needs into practical data solutions Building solutions: designing, building and optimizing scalable dbt-based data pipelines, transformations and logical and physical data models Who are we looking for? We are looking for an experienced data engineer who enjoys hands-on building but also thinks about the bigger picture, and who genuinely wants to help others grow. We Are Not Looking For Unicorns, But The More Of Below Capabilities Are Found The Better You’d Fit To The Ideal Candidate Profile Snowflake, dbt and SQL: strong hands-on experience in data engineering with Snowflake, proficiency with dbt for transformations, efficient SQL skills and solid data modelling capability. (This one is actually mandatory) Modern engineering practices: experience with version control, CI/CD pipelines and a DevOps mindset in a data context; what we develop, we also support. Background in data warehousing/ETL: You have designed or maintained data pipelines with different technologies. Experience with SAP BW data models and transformations is beneficial, as it helps in understanding our legacy environment. Data management mindset: Familiarity with data cataloging, lineage tools, semantic views, or overall data governance frameworks. You care about documentation and data quality. Big picture view: the ability to make sound technical choices across source data, data modelling, transformations and reporting needs, not just build individual pipelines. Mentoring ability: experience and motivation in sharing knowledge, supporting colleagues and contributing to the development of data engineering practices AI mindset: interest in leveraging AI to speed up and improve development and maintenance processes Communication: excellent teamwork and communication skills, and the ability to explain complex data topics to both technical and non-technical colleagues. Fluency in English is required (our working language). Finnish or other Nordic language skills are beneficial but not necessary. Self-driven and proactive attitude: You take initiative to improve things and aren’t afraid to suggest new ideas. You are solution-oriented and able to work independently when needed, but also know when to ask for help or input. Relevant experience with SAP, Aspect4 or web-based business application data as well as familiarity with chain-operated wholesale and/or merchant-led retail business models, especially in the building and technical trade sector Please note that the role is in Finland and you will need the existing right to work here.