Data Engineer (Freelance)

DevologyX; München; Hybrid; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading company in the FinTech space is seeking a Data Engineer to design, develop, and maintain data pipelines that empower analytics and decision-making. You will collaborate with AI engineers and data scientists, ensuring robust data infrastructure while optimizing data solutions using modern technologies.

Leistungen

Work on high-impact financial data projects

Qualifikationen

• Strong SQL and Python skills for data processing.
• Experience with modern data lake and warehouse solutions.
• Proficiency in cloud-based data engineering.

Aufgaben

• Develop and maintain ETL / ELT pipelines using Apache Airflow.
• Optimize data storage and processing with Snowflake and Databricks.
• Work with Kafka for real-time data streaming.

Kenntnisse

SQL

Python

Data modeling

Data quality

Data governance

Tools

Apache Airflow

Snowflake

Databricks

Kafka

AWS

GCP

Azure

Jobbeschreibung

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 / ELT 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

• 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.