AI Data Engineer (Snowflake + AI)

Nordea Bank Norge ASA; Warszawa; On-site; PLN 80,000 - 120,000; Full time

Job summary

Nordea Bank Norge ASA in Warsaw is seeking a Data Engineering role focused on AI processes and Snowflake integration. The candidate will define and implement AI features and work closely with Snowflake Cortex to enhance data usage across the platform.

The ideal candidate has extensive experience in data engineering, a strong background in SQL and Snowpark, and a proven track record of working with LLMs. This position is critical as we evolve our approach to data.

Additional benefits include a collaborative work environment fostering ownership and creativity.

Qualifications

• 8+ years in data engineering or ML engineering with production Snowflake experience.
• Strong SQL and Snowpark (Python or Scala).
• At least 1 year working with LLMs in production—API integrations, structured outputs.
• Practical experience with Snowflake Cortex, Anthropic API, OpenAI API, or Azure OpenAI.

Responsibilities

• Define and establish AI processes around our data.
• Build LLM-powered features in Streamlit on Snowflake.
• Work with Snowflake Cortex to integrate AI capabilities.
• Develop AI-assisted tooling for the engineering team.

Skills

Data engineering

Machine learning engineering

SQL

Snowpark (Python/Scala)

LLM integration

Snowflake Cortex

Tools

Airflow

Bitbucket

CI/CD

Job description

Job ID: 4087

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 place where traditions meet tomorrow. We’re not just a bank, we’re a tech employer on a mission to evolve finance securely and responsibly.

About our team: The main goal of this role is to help us build and establish AI processes around our data. We work on financial and regulatory datasets in Snowflake and we want to start using AI meaningfully— not as a productivity gimmick, but as a serious part of how we work with data: surfacing insights, assisting engineers, and empowering business users who interact with our data platform.

You’ll own this space. That means figuring out what’s worth building, what’s feasible within a regulated banking environment, and then actually building it— from Snowflake Cortex integrations to LLM‑assisted tooling for the engineering team to AI‑powered features in our Streamlit self‑service platform.

Main responsibilities

• Define and establish AI processes around our data—identify where AI adds real value, design the approach, and own the implementation.
• Understand MCPs, Context Engineering and relevant tools that support LLM integrations.
• Have experience in productionized Agentic AI solutions with market/Industry standards decision‑making Agents.
• Build LLM‑powered features into our Streamlit‑in‑Snowflake platform (e.g. natural‑language query interfaces, anomaly detection, schema explanation for business users in Finance and Risk).
• Work with Snowflake Cortex (LLM functions, Cortex Search, Cortex Analyst) to bring AI capabilities directly into our Snowflake environment.
• Design RAG pipelines over our structured and semi‑structured data—metadata catalogs, transformation configs, code repositories.
• Develop AI‑assisted tooling for the engineering team: SQL review assistants, documentation agents, test generators.
• Contribute to team AI practices—how we use Copilot, what context we maintain, how we evaluate output quality.
• Build and maintain Snowflake transformation pipelines alongside AI work—stored procedures, Snowpark (Python/Scala), Dynamic Tables.
• Engage in requirement analysis—understand domain and data context before building solutions.

Who you are

Must have

• 8+ years in data engineering or ML engineering with production Snowflake experience.
• Strong SQL and Snowpark (Python or Scala).
• At least 1 year working with LLMs in production—API integrations, structured outputs, tool use, retrieval.
• Practical experience with Snowflake Cortex, Anthropic API, OpenAI API, or Azure OpenAI.
• Airflow, Bitbucket, CI/CD—end‑to‑end ownership, not just code delivery.

Nice to have

• Agentic frameworks (LangGraph, Claude Agent SDK).
• Streamlit in Snowflake.
• LLM evaluation frameworks (LLM‑as‑judge, golden sets, prompt regression testing).
• Financial services or banking domain knowledge—credit risk, finance, or regulatory data background.

Mindset

• Comfortable working across the full delivery lifecycle—analysis, development, testing, deployment.
• Thoughtful about cost, latency, and determinism when designing AI features.

Working with AI

• Genuine fluency with LLMs—understands how they work, where they’re useful, and where they fail.
• Actively tracks the AI tooling market: new models, coding assistants, Snowflake Cortex updates, agentic frameworks.
• Knows how to maintain context files and prompt standards so the whole team benefits from AI tooling, not just the person who figured it out.
• Treats AI output as a starting point—reviews, tests, and owns what gets committed.

What we offer

Collaboration. Ownership. Passion. Courage. These are the values that guide us in how we work and how we make decisions – and that we imagine you share with us.

Location and legal considerations

Only for candidates in Finland: A security clearance will be performed for the person selected for this position.

Only for candidates in Poland: Please include a permit for processing personal data in your CV.

We reserve the right to reply only to selected applications.