EPAM Systems
, , Denmark / Global
Team Lead Data Engineering - Snowflake / AWS
- kr.900.000 - kr.1.200.kr.000
- Hybrid
, , Denmark / Global
You will architect and optimize scalable data pipelines, datasets and analytical workflows at EPAM in Copenhagen, Denmark, working in a hybrid model. Initially at one of our Clients in the Advanced Manufacturing / Life Sciences space. Using Snowflake, Dataiku, SQL and Python, you enable feature engineering for machine learning and support robust data products for analytics and business intelligence. You collaborate with data science, product and delivery teams to deliver production-ready solutions with a focus on data quality, performance and maintainability.
Responsibilities Build and maintain scalable data pipelines and analytical workflows using Snowflake and Dataiku
Write and optimize SQL for data transformation, feature engineering and analytical use cases
Develop and maintain data models, datasets and views in Snowflake for downstream consumption
Create, validate and maintain reusable features in Dataiku for machine learning models
Leverage existing features and datasets to reduce duplication and improve consistency
Implement automated testing, monitoring and CI/CD for production data pipelines
Ensure data quality and follow enterprise data governance and security standards
Troubleshoot data issues across pipelines, including upstream AWS services
Support data requirements for analytics, reporting and business intelligence
Collaborate with data science, product and delivery teams to translate business needs into reliable data solutions
Requirements 6-8+ years of Data Engineering experience at Enterprise scale
Hands-on experience with Snowflake and Dataiku
Strong SQL skills, including query optimization and data transformation
Proficiency in Python for data engineering workflows
Experience building and maintaining production data pipelines
Solid understanding of data modeling and feature engineering for analytics and machine learning
Experience with automated testing, monitoring and CI/CD for data pipelines
Familiarity with AWS data services, such as Lambda, S3, Glue and Step Functions, for troubleshooting upstream pipelines
Ability to work effectively within governed enterprise environments
Strong problem-solving skills and ability to collaborate across technical and business teams
Nice to have Experience in healthcare, life sciences or customer-support analytics
Familiarity with feature stores and reusable feature management
Experience supporting business intelligence and reporting datasets
#J-18808-Ljbffr
København / Global
, Denmark / Global
København / Global
København / Global
København / Global
København / Global