
Data Engineer
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("In Helsinki, Finland: Data Engineer"), this listing's salary midpoint is about 91% lower. The offer sits below the benchmark range (€3,000–€6,850). The listed pay band (€354–€500) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 14 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Data Engineer | €2,990/per month | €5,125/per month | €7,204/per month |
| In Helsinki, Finland: Data Engineer | €3,000/per month | €5,125/per month | €6,850/per month |
| Pay in our data — not quoted in ad (Senior) | €354/per month | €427/per month | €500/per month |
We are looking for a Senior Data Engineer to join our Feature Engineering team. You will play a key role in transforming big and complex data into meaningful features that enables machine learning model to predict patterns to fight against financial crime. About our team Meet the Data and Platform team. Our role is to build robust data and platform foundation to enable threat detection capabilities, keeping our customers, Nordea and society safe. Our team is about 30 people as a part of the group financial crime prevention (GFCP) unit that provides financial crime prevention services to all of the bank. 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. What youll be doing: - Design, build, and optimize scalable data pipelines handling large volumes of data - Utilize AWS technologies to create and maintain efficient data transformation workflows - Work closely with data scientists, platform and data specialists - Ensure the solutions meet data quality and governance standards - Document and communicate the results of your efforts Who are you We believe that you're ambitious and enjoy bringing ideas, exploring their potential, and presenting the results. You're passionate about designing and building data pipelines to produce features for machine learning models to identify complex financial crimes, ensuring both the banks and society's safety. Your experience and background: - At least 5 years of experience creating and optimizing data pipelines and processing large data sets - Experience with AWS and services: Glue, S3, Athena, Step Functions and Event Bridge - Proficiency in Python, PySpark and SQL - A degree in data engineering, computer science or related field - Self-driven team player with curious mindset - Ability to communicate clearly on complex topics - Fluency in English What we offer A culture that fosters performance and growth in one of the largest Nordic banks, offering various opportunities to evolve, develop and learn from brilliant colleagues with diverse backgrounds in a vibrant working environment. Hybrid working model we believe in the value of bringing people together and at the same time we embrace the freedom of flexibility. Diversity and inclusion are a natural part of our daily work.
Job Details
Responsibilities
- Design, build, and optimize scalable data pipelines handling large volumes of data
- Utilize AWS technologies to create and maintain efficient data transformation workflows
- Work closely with data scientists, platform and data specialists
- Ensure the solutions meet data quality and governance standards
- Document and communicate the results of your efforts
Requirements
- At least 5 years of experience creating and optimizing data pipelines and processing large data sets
- Experience with AWS services: Glue, S3, Athena, Step Functions and Event Bridge
- Proficiency in Python, PySpark and SQL
- A degree in data engineering, computer science or related field
- Self-driven team player with curious mindset
- Ability to communicate clearly on complex topics
- Fluency in English
Skills & Technologies
Education Level
BachelorBenefits & Perks
Recruitment Process
- 1Interviews on ongoing basis

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