Data Engineer: Cloud-Driven Pipelines & ML

Future Impact; Amsterdam; On-site; EUR 65,000 - 95,000; Full time

Job summary

Knab is building a cloud-based Intelligence Infrastructure with a Data lake at its core and is looking for a Data Engineer to join the Expert Center Data. You will partner with Data Scientists, Cloud Engineers and the Data Management Team to build and productionize data-intensive systems that deliver value for customers.

The role emphasizes Python proficiency and knowledge of tools like Apache Airflow, Hadoop and Spark, with exposure to AWS Glue, SageMaker, Lambda and DMS, and collaboration

Qualifications

• Master degree in a quantitative field with strong analytical skills.
• Proficient Python coding for data engineering tasks.
• Nice to have knowledge of open source data tooling and cloud services.
• Analytical abilities that help develop innovative data solutions.

Responsibilities

• Setup, deployment and productionizing of data-intensive systems in close collaboration with Data Scientists, Cloud Engineers and Data Management Team.
• Engineering systems, from the OS-level to big data clusters.
• Develop data pipelines including transformation and pre-processing.
• Work in multidisciplinary teams of marketers, online marketers, analysts and developers, so that you are closely involved in the business.

Skills

Excellent Python coding skills

Analytical abilities

Education

Master degree in quantitative field (Econometrics, Physics, Mathematics, Artificial Intelligence, Operations Research, etc.)

Tools

Apache Airflow

Hadoop

Spark

AWS Glue

AWS Sagemaker

AWS Lambda

AWS DMS

Job description

Knab is building a cloud-based Intelligence Infrastructure with a Data lake at its core and is looking for a Data Engineer to join the Expert Center Data. You will partner with Data Scientists, Cloud Engineers and the Data Management Team to build and productionize data-intensive systems that deliver value for customers.

The role emphasizes Python proficiency and knowledge of tools like Apache Airflow, Hadoop and Spark, with exposure to AWS Glue, SageMaker, Lambda and DMS, and collaboration