Python Data Engineer: SAS-to-Python Modernization (Remote)

Katmai Government Services; United States; On-site; USD 145,000 - 150,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) Savings Plan

Paid holidays

Paid time off

Job summary

Katmai Government Services seeks a data engineer to modernize core data processing, translating SAS logic into Python for scalable pipelines in a cloud-native AWS environment. You will ensure data accuracy, maintainability, and robust documentation while handling large-scale datasets.

The role involves end-to-end data pipelines, larger-than-memory processing, and PostgreSQL integration, with emphasis on testing, validation, and collaboration with IT specialists to deliver reliable data products.

Qualifications

• Ability to read and interpret SAS code.
• Experience with Parquet, SQL, JSON, and larger-than-memory datasets.
• Experience with libraries like 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.

Responsibilities

• Translate SAS logic to Python with functional parity and improved maintainability.
• Design and develop end-to-end data pipelines for ingestion, cleaning, validation, and transformation of diverse data formats.
• Profile, optimize, and refactor code; implement parallel computing with Dask and multiprocessing.
• Develop Python solutions interfacing with PostgreSQL for high-volume data storage and processing.
• Implement automated testing, data validation, and QA processes to ensure data integrity.

Skills

SAS programming

Python

SQL

Linux

AWS

Parquet

Dask

Profiling

Unit testing

Documentation

Education

Bachelor's degree in CS

Tools

PySpark

PostgreSQL

Git

Parquet

Dask

Job description

Katmai Government Services seeks a data engineer to modernize core data processing, translating SAS logic into Python for scalable pipelines in a cloud-native AWS environment. You will ensure data accuracy, maintainability, and robust documentation while handling large-scale datasets.

The role involves end-to-end data pipelines, larger-than-memory processing, and PostgreSQL integration, with emphasis on testing, validation, and collaboration with IT specialists to deliver reliable data products.