Job summary
Seeking a Senior Data Engineer experienced in building and maintaining large-scale data and machine learning pipelines. The role focuses on developing scalable ETL workflows and ML infrastructure primarily using Python and AWS cloud services. Collaboration with data scientists and ML engineers to productionize forecasting models is key, within an Agile, distributed team environment.
Location and work setup
- Location
- Norway
- Work setup
- Remote
Responsibilities
Develop and maintain production-grade data and machine learning pipelines supporting forecasting and data-driven decisions. Implement scalable ETL workflows in Python. Design and manage workflow orchestration using Apache Airflow and AWS Step Functions. Utilize AWS Glue for data processing and transformation. Support deployment and operationalization of machine learning models with AWS SageMaker. Monitor and troubleshoot pipeline performance and reliability issues. Contribute to architectural and technical improvements across the data platform. Work collaboratively in distributed, cross-functional Agile teams.
Qualifications
Strong experience with Python applied to data engineering and production systems. Proven ability to build and maintain data and ML pipelines in production environments. Hands-on expertise with Apache Airflow, AWS Step Functions, AWS Glue, and AWS SageMaker. Solid understanding of AWS cloud services and managing scalable, reliable systems. Capability to work closely with data scientists and ML engineers. Strong analytical, problem-solving, and communication skills in English. Experience with GCP and monitoring tools is a plus but not mandatory.