Python Data Engineer

Job Description: SAS / Python Data Engineer

Experience: 10+ Years
Job Type: Full-Time
Role: SAS / Python Data Engineer

Role Overview

We are looking for an experienced SAS / Python Data Engineer with 5+ years of hands-on experience in data engineering, data processing, analytics, and ETL development. The ideal candidate should have strong expertise in SAS and Python, along with experience in building scalable data pipelines, data transformation processes, and integrating data from multiple sources.

The candidate will work closely with data analysts, business teams, and technology teams to design, develop, and maintain reliable data solutions.

Key Responsibilities

Design, develop, and maintain robust ETL/ELT data pipelines using SAS and Python.

Develop and optimize SAS programs for data extraction, transformation, validation, and reporting.

Build Python-based data processing and automation solutions.

Extract and integrate data from databases, flat files, APIs, and other data sources.

Perform data cleansing, transformation, aggregation, and validation.

Develop reusable Python scripts and frameworks for data engineering and automation.

Optimize SAS and Python code for performance, scalability, and maintainability.

Work with large datasets and implement efficient data processing techniques.

Develop and maintain SQL queries, stored procedures, and data transformations.

Perform data quality checks and troubleshoot data discrepancies.

Participate in data migration, integration, and modernization initiatives.

Collaborate with cross-functional teams to understand business and technical requirements.

Monitor data pipelines and resolve production issues within defined SLAs.

Create technical documentation for data pipelines, processes, and solutions.

Follow coding standards, version control, testing, and deployment best practices.

Required Skills
SAS

5+ years of hands-on experience with SAS programming.

Strong knowledge of Base SAS, SAS SQL, DATA Step, PROC SQL, and macros.

Experience with SAS data manipulation, transformation, and optimization.

Knowledge of SAS ETL processes and batch processing.

Experience working with large datasets.

Python

Strong hands-on experience with Python for data engineering and automation.

Experience with libraries such as Pandas, NumPy, and other data-processing frameworks.

Ability to develop reusable and production-ready Python scripts.

Experience with error handling, logging, debugging, and performance optimization.

Data Engineering & SQL

Strong understanding of ETL/ELT concepts and data pipelines.

Strong SQL skills with experience in complex queries, joins, subqueries, CTEs, and window functions.

Experience working with relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.

Understanding of data warehousing concepts, dimensional modeling, and data quality.

Experience with batch processing and scheduling tools.

Preferred Skills

Experience with cloud platforms such as AWS, Azure, or GCP.

Exposure to Spark/PySpark.

Experience with tools such as Databricks, Airflow, Azure Data Factory, AWS Glue, or similar data engineering platforms.

Knowledge of Git and CI/CD practices.

Experience with Linux/Unix shell scripting.

Understanding of REST APIs and data integration.

Exposure to Agile/Scrum development methodologies.

Desired Candidate Profile

5+ years of professional experience in SAS, Python, SQL, and data engineering.

Strong analytical and problem-solving skills.

Ability to work independently as well as collaboratively.

Good communication and stakeholder-management skills.

Strong attention to data accuracy and quality.

Ability to troubleshoot complex technical and data-related issues.

Comfortable working in a fast-paced, delivery-oriented environment.