Snowflake Data Engineer

Nordea; Helsinki; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Nordea is hiring for a Senior Data Engineer to join the Large Data Foundation within Group Technology. You will design and implement transformation pipelines on Snowflake, ensuring clean, governed analytics datasets for risk model development.

Bring 8+ years in data engineering with 2+ years Snowflake production experience, plus strong SQL, Snowpark, Python/Scala, and Airflow skills. Hybrid work model offered with emphasis on collaboration and auditability.

Qualifications

• 8+ years in data engineering or related field.
• 2+ years with Snowflake in production.
• Strong SQL including window functions, QUALIFY, MERGE and recursive CTEs.
• Experience with Snowpark (Python or Scala).
• Understanding of Snowflake execution model and clustering.
• Proficiency in Python or Scala for pipelines.
• Airflow experience (DAGs, sensors, retries).
• Comfort with Git, Bitbucket, and CI/CD deployments.

Responsibilities

• Design and build transformation jobs in Snowflake (SQL stored procedures, Snowpark, Dynamic Tables).
• Analyze business and data requirements before coding.
• Translate requirements into clean, maintainable transformation logic.
• Apply Snowflake best practices: clustering, micro-partition awareness, query optimization, rightsizing.
• Contribute to data modeling decisions (schema design, naming conventions, partitioning strategies).
• Own CI/CD for deliverables (branching, deployments, promotion via Bitbucket and Jenkins).
• Write and maintain Airflow DAGs that orchestrate Snowflake workloads.
• Contribute to the data exchange layer (Database Roles, Secure Views, cross-account sharing).
• Review code, pair with team members, contribute to team standards.

Skills

SQL proficiency

Snowflake experience

Python/Scala

Airflow

Git/CI/CD

Data modeling

Performance tuning

Tools

Snowpark

Git

Bitbucket

Airflow

Job description

Overview

Join the Large Data Foundation team in Group Technology at Nordea. We build and maintain transformation layers on Snowflake to produce clean, governed, analytics‑ready datasets for risk model development and parameter use.

Responsibilities

• Design and build transformation jobs in Snowflake (SQL stored procedures, Snowpark, Dynamic Tables).
• Analyze business and data requirements before coding.
• Translate requirements into clean, maintainable transformation logic.
• Apply Snowflake best practices: clustering, micro‑partition awareness, query optimization, warehouse rightsizing.
• Contribute to data modeling decisions (schema design, naming conventions, partitioning strategies).
• Own CI/CD for deliverables (branching, deployments, promotion via Bitbucket and Jenkins).
• Write and maintain Airflow DAGs that orchestrate Snowflake workloads.
• Contribute to the data exchange layer (Database Roles, Secure Views, cross‑account sharing).
• Review code, pair with team members, contribute to team standards.

Qualifications

• 8+ years in data engineering, 2+ years with Snowflake in production.
• Strong SQL (window functions, QUALIFY, MERGE, recursive CTEs, FLATTEN/LATERAL, performance tuning).
• Experience with Snowpark (Python or Scala).
• Understanding of Snowflake execution model (micro‑partitions, clustering, pruning, query plan).
• Proficiency in Python or Scala for pipeline logic.
• Airflow experience (DAGs, sensors, retries).
• Comfort with Git, Bitbucket, CI/CD deployments.
• Knowledge of financial services or banking, especially credit risk, finance, or regulatory reporting.

Nice to Have

• Snowflake Dynamic Tables, Streams, Tasks, Snowpipe.
• Experience with DataStage, Streamlit in Snowflake.
• Agile (SAFe or other scaled agile) experience.

Mindset

• Work across the full delivery lifecycle: analysis, development, testing, deployment.
• Choose the simplest Snowflake feature that solves the problem.
• Optimize based on query profiles, not guessing.
• Include auditability, lineage, and access controls in design.

Working with AI

• Use AI coding tools daily.
• Understand LLMs to use effectively and know when to trust or revise output.
• Stay updated on AI tooling market and relevance to data engineering.

Benefits & Culture

Nordea offers a hybrid work model that balances collaboration and flexibility. The organization values collaboration, ownership, passion, and courage, fostering an environment where employees can grow and take their careers to the next level. Diversity and inclusion are core to our culture, and we are committed to creating an inclusive workplace where all individuals can thrive.