12 Month Contract, Possible Extension, Occassional Onsite in Frankfurt needed once per quarter (TBD)
As a Data Engineer in the FinTech space, you will design and maintain data pipelines that power analytics, machine learning, and real-time financial decision-making.
You will work with modern data engineering technologies to process, transform, and optimize financial datasets at scale.
Collaborating with AI engineers and data scientists, you will play a key role in building robust data infrastructure.
RESPONSIBILITIES
Develop and maintain ETL pipelines using Apache Airflow.
Optimize data storage and processing with Snowflake, Databricks.
Work with Kafka or Pulsar for real-time data streaming.
Implement data quality and governance best practices.
Deploy scalable data solutions on AWS, GCP, or Azure.
Collaborate with analytics teams to support business intelligence initiatives
REQUIREMENTS
5-7+ Years as a Data Engineer
Strong SQL and Python skills for data processing.
Experience with modern data lake and warehouse solutions (Snowflake, BigQuery, Redshift).
Knowledge of real-time data processing (Kafka, Pulsar, Spark Streaming).
Proficiency in cloud-based data engineering.
Understanding of data modeling and schema design.
NICE TO HAVE
Familiarity with FinTech regulations and compliance.
Experience with DBT for data transformation workflows.
Exposure to MLOps and AI-driven analytics.
BENEFITS
Work on high-impact financial data projects.