Lead Python Data Engineer

Experience level 10+ years.
Design, architect, and implement robust and scalable data pipelines using Python and related technologies (Airflow, PySpark, PyFlink are a plus).
Champion best practices for data engineering, code quality, testing, and deployment.
Mentor and guide a team of talented data engineers, fostering a collaborative and high-performing team culture.
Collaborate closely with Data Scientists, Data Analysts, and business stakeholders to translate complex business requirements into efficient data solutions.
Continuously research and implement new technologies and best practices to improve the efficiency and scalability of our data platform.
Take ownership of the deployment and monitoring of data pipelines and related infrastructure on cloud platforms such as Openshift, ECS, or Kubernetes.

Lead the design and development of data pipelines for ingestion, transformation, and loading of data from various sources (databases, APIs, streaming platforms) into our data warehouse/lake.
Write optimized and maintainable SQL queries and leverage SQLAlchemy for efficient database interaction.
Implement robust data quality checks and monitoring systems to ensure data integrity and accuracy.
Develop comprehensive documentation and contribute to knowledge sharing within the team.
Contribute to the design and implementation of data governance policies and procedures.

Experience with data visualization tools and techniques.
Familiarity with agile development methodologies.
Contributions to open-source projects or active participation in the data engineering community.
Banking / Financial experience is preferred.