Data Engineer (Freelance)

DevologyX; Österreich; Vor Ort; USD 150 000 - 195 000; Vollzeit

Zusammenfassung

A leading company in the FinTech sector is seeking a Data Engineer to design and maintain critical data pipelines that support analytics and machine learning. The role requires strong SQL and Python skills, along with experience in modern data engineering technologies like Snowflake and Apache Airflow. The position offers an opportunity to collaborate with AI engineers and data scientists in a dynamic environment focused on real-time financial decision-making.

Leistungen

Work on high-impact financial data projects.

Qualifikationen

• Strong SQL and Python skills for data processing.
• Experience with Snowflake and Kafka for data solutions.
• Proficiency in cloud data engineering.

Aufgaben

• Develop and maintain ETL/ELT pipelines using Apache Airflow.
• Optimize data storage and processing with Snowflake and Databricks.
• Collaborate with analytics teams to support business intelligence initiatives.

Kenntnisse

SQL

Python

Data Modeling

Data Governance

Tools

Apache Airflow

Snowflake

Kafka

AWS

Jobbeschreibung

12 Month Contract, Possible Extension. Onsite visits in Frankfurt, once per quarter (TBD / Not 100% Mandatory)

• 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.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Staffing and Recruiting

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