Snowflake Expert Engineer
Listed on 2026-06-02
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IT/Tech
Data Engineer
Job
Welcome to Group Technology, where we pride ourselves on engineering solutions and direct Nordea’s transformation by providing a holistic technological view and structured understanding of the bank, and its surrounding environment to enable the Customer Vision and the Business Strategy.
Nordea is a tech employer on a mission to evolve finance securely and responsibly.
About our teamThis is a depth role. While everyone on the team builds on Snowflake, you're the person who sets the standard — for transformation patterns, performance, governance, and platform decisions. You know Snowflake deeply enough to know which feature to use, which to avoid, and why. You make architectural calls before anyone writes code and align Technology Product lead, and you're still happy to sit with a junior engineer on their PR afterwards.
We work cross-functionally — senior engineers are expected to contribute across the full delivery lifecycle: from requirements elicitation and credit risk data domain understanding, through development and code review, to owning CI/CD standards and deployment practices for the team. You'll be joining a team that values knowledge sharing seriously — there's a strong culture of pairing, design reviews, and internal documentation.
You'll both benefit from that and be expected to contribute to it.
- Set technical standards for Snowflake transformations — when to use Dynamic Tables vs Tasks vs stored procedures vs Snowpark, and the tradeoffs of each
- Deep dive into Data and come up with technical solutions to align with Business requirements
- Contribute to and review requirement analysis — bridge domain knowledge and technical implementation
- Deep-dive performance work: query profiling, micro-partition analysis, clustering design, warehouse rightsizing, spill elimination
- Lead governance: RBAC hierarchy, Database Roles, masking policies, row access policies, tag-based governance
- Design and evolve the data sharing architecture (Secure Views, Reader Accounts, cross-account sharing for downstream teams)
- Drive and own CI/CD standards for Snowflake: schema change, Terraform, or equivalent integrated with Bitbucket/Jenkins
- Mentor mid-level engineers, run design reviews and brown-bags
- Partner with team lead on PI Planning, roadmap, and technical decisions
Must have:
- 10+ years in data engineering, with at least 3 years Snowflake at meaningful production scale
- Key understanding of Data knowledge and be able to perform Data analysis and be able to design and lead Technical solutions
- Snow Pro Core certified;
Snow Pro Advanced:
Data Engineer strongly preferred - Deep SQL mastery: query plan interpretation, QUALIFY, , recursive CTEs, advanced VARIANT/OBJECT/ARRAY handling, window functions, lateral joins
- Snowpark (Python or Scala) — knows when it's the right call and when SQL is better
- Strong grasp of Snowflake internals: micro-partitions, clustering, pruning, result caching, warehouse credit consumption
- Dynamic Tables, Streams, Tasks — has used all three in production and can articulate when each is appropriate
- Governance: RBAC, Database Roles, masking policies, row access policies
- CI/CD for Snowflake: schema change, Terraform, or equivalent — owns it, doesn't just use it
- Financial services or banking domain knowledge — credit risk, finance, or regulatory reporting. At senior level, domain understanding directly influences architectural decisions
- Credit risk functional knowledge
- Airflow in a Snowflake-heavy environment
- Data Stage (legacy interop context)
- Snowflake Cortex, Snowpipe Streaming
- Comfortable working across the full delivery lifecycle — analysis, architecture, development, CI/CD, deployment
- Treats the platform as a product — reliability, cost, and developer experience all matter equally
- Documents decisions, not just code — architecture records, naming conventions, runbooks
- Uses AI tooling confidently and sets an example for the team on how to do it well
- Understands context engineering — knows that good AI output starts with good context, and helps maintain the repo-level files that make that possible
- Tr…
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