We are looking for an intermediate-level Python developer in data engineering to design, build, and maintain scalable data pipelines for a financial services client in New York. You will work with cross-functional, cross-regional teams to implement data extraction, transformation, and loading (ETL) processes, develop APIs, and optimize data workflows for large datasets.

Responsibilities

Qualifications:

Design, develop, and implement software applications and scalable data pipelines using Python and related technologies.
Optimize data workflows to handle large datasets efficiently.
Write clean, efficient, and maintainable code; document APIs.
Develop and manage databases and applications; implement ETL processes.
Write and document effective APIs; test software at scale to ensure responsiveness and efficiency.
Ensure data accuracy, consistency, and completeness; identify and resolve data issues.
Collaborate with team members, stakeholders, and other developers to define requirements and solutions; participate in code reviews.
Troubleshoot, debug, and upgrade software; address performance issues and bugs.
Contribute to project documentation.
Proficiency in Python with solid object-oriented programming skills.
Experience with data libraries (Django, Flask, NumPy, Pandas) and databases (PostgreSQL, MySQL; NoSQL like MongoDB).
Familiarity with data storage technologies (data lakes, distributed file systems).
Knowledge of ETL tools (Apache Airflow, Apache Kafka)

About the role

Python Developer – Data Engineering (On-site, New York, United States)

We are looking for an intermediate-level Python developer in data engineering to design, build, and maintain scalable data pipelines for a financial services client in New York. You will work with cross-functional, cross-regional teams to implement data extraction, transformation, and loading (ETL) processes, develop APIs, and optimize data workflows for large datasets.

Responsibilities

Qualifications:

Design, develop, and implement software applications and scalable data pipelines using Python and related technologies.
Optimize data workflows to handle large datasets efficiently.
Write clean, efficient, and maintainable code; document APIs.
Develop and manage databases and applications; implement ETL processes.
Write and document effective APIs; test software at scale to ensure responsiveness and efficiency.
Ensure data accuracy, consistency, and completeness; identify and resolve data issues.
Collaborate with team members, stakeholders, and other developers to define requirements and solutions; participate in code reviews.
Troubleshoot, debug, and upgrade software; address performance issues and bugs.
Contribute to project documentation.
Proficiency in Python with solid object-oriented programming skills.
Experience with data libraries (Django, Flask, NumPy, Pandas) and databases (PostgreSQL, MySQL; NoSQL like MongoDB).
Familiarity with data storage technologies (data lakes, distributed file systems).
Knowledge of ETL tools (Apache Airflow, Apache Kafka)

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