Python Data Engineer: Modernize SAS, Scalable Pipelines

Katmai; United States; Remote; USD 145,000 - 150,000; Full time

Benefits offered by this job

Remote-friendly

Job summary

Katmai is seeking a seasoned Data Engineer to lead the modernization of core data processing systems. You will translate SAS logic into robust Python solutions and build scalable pipelines for large-scale datasets in a cloud-native environment.

You will work with DSD IT Specialists in an integrated team to deliver maintainable and high-performance data products, with emphasis on quality, documentation, and collaboration.

Qualifications

• Ability to read and interpret SAS code.
• Experience with Parquet, SQL, JSON, and larger-than-memory datasets.
• Experience with PySpark, multiprocessing, Dask, and code profiling tools.
• Experience in Linux environments and cloud-native resources (e.g., AWS).
• Strong SQL skills, specifically with PostgreSQL integration.
• Version control (Git), unit testing, and technical documentation.
• Experience using Python to read and reformat large data files.
• Experience improving code performance, including profiling and refactoring code to identify bottlenecks and overhead, preferably in production environments.
• Experience writing high-quality code that is well-documented and easy to read, use, maintain, and extend.

Responsibilities

• Analyze existing SAS-based systems and re-implement logic in Python, ensuring functional parity while improving maintainability, scalability, and performance.
• Design and develop end-to-end data pipelines to ingest, clean, validate, and transform diverse data formats—including SAS datasets, Parquet, JSON, and SQL—using larger-than-memory processing techniques.
• Profile, optimize, and refactor code to eliminate bottlenecks and improve performance. Implement parallel computing strategies using libraries such as Dask and multiprocessing to efficiently process production-scale workloads.
• Develop Python solutions that interface with PostgreSQL for high-volume data storage, retrieval, and processing.
• Implement automated testing, data validation, and quality assurance processes to ensure the integrity, accuracy, and reliability of critical data assets throughout the data lifecycle.
• Maintain high standards for code quality by producing well-documented, readable, maintainable, and extensible code. Participate in peer reviews and knowledge sharing to promote engineering best practices.
• Collaborate with DSD IT Specialists and other stakeholders to implement efficient, scalable Python solutions that meet functional and technical requirements.
• Partner with DSD stakeholders to validate business and technical requirements, troubleshoot implementation issues, and support the successful modernization of legacy systems.
• Attend branch meetings and communicate technical concepts, project updates, and recommendations clearly and effectively.
• Maintain regular communication with the team as required.
• Maintain regular and punctual attendance.
• Perform other duties as assigned.

Skills

SAS reading

Python data processing

Data pipeline design

Performance optimization

Cloud computing AWS

SQL & PostgreSQL

Linux proficiency

Testing & QA

Documentation

Education

Bachelor's degree in CS or related field

Tools

PySpark

Dask

PostgreSQL

Git

AWS

Parquet

JSON

SQL

Job description

Katmai is seeking a seasoned Data Engineer to lead the modernization of core data processing systems. You will translate SAS logic into robust Python solutions and build scalable pipelines for large-scale datasets in a cloud-native environment.

You will work with DSD IT Specialists in an integrated team to deliver maintainable and high-performance data products, with emphasis on quality, documentation, and collaboration.