T&T – Engineering – Consultant – Statistical Analysis System Data engineer – Multiple Location

Role Overview

The SAS framework data engineer is responsible for managing client relationships and overseeing the successful delivery of programs or accounts. This role serves as the primary point of contact between the organization and its clients, ensuring alignment of goals, timelines, budgets, and expected outcomes while driving client satisfaction and business growth.

What You Will Do

Key responsibilities include migration of SAS frameworks to Databricks/PySpark, design and development of PySpark pipelines from SAS macros, implementation of validation frameworks between SAS and Spark outputs, and management of DevOps lifecycle with Git/Bitbucket integration.

Why It Might Be a Fit

The ideal candidate will have strong hands-on experience with AWS cloud services, proficiency in Python (PySpark), SQL, and data transformation logic, and knowledge of Spark (EMR/Glue) and distributed data processing.

Requirements

• 3+ years of strong hands-on experience with Migration of SAS frameworks to Databricks/PySpark
• Proficiency in Python (PySpark), SQL, and data transformation logic
• Design and develop PySpark pipelines from SAS macros
• Managing DevOps lifecycle with Git/Bitbucket integration, code reviews, and production deployments
• Design, build, and maintain scalable data pipelines on AWS
• Partnered with cross-functional teams to translate business requirements into technical delivery plans
• Build and optimize data lakes using S3, Glue Catalog, and Lake Formation
• Work with Redshift/Snowflake for data warehousing solutions
• Implement data quality checks, monitoring, logging, and CI/CD deployments
• Collaborate with analytics and business teams to deliver high-quality datasets
• Strong hands-on experience with AWS cloud services
• Proficiency in Python (PySpark), SQL, and data transformation logic
• Experience with Redshift, Athena, and Glue Data Catalog
• Knowledge of Spark (EMR/Glue) and distributed data processing
• Familiarity with Terraform/CloudFormation for IaC is a plus
• Good understanding of data modeling, data lake principles, and best practices
• Design, develop and deploy solutions using different tools, design principles and conventions
• Understand existing processes and facilitate changing requirements as part of a structured change control process
• Maintain proper documentation for the solutions, test procedures and scenarios during UAT and Production phase
• Coordinate with process owners and business to understand the as-is process and design the automation process flow

Tagged as: Python, Snowflake, SQL