Apply for Data Analytics Engineer Job

4–6 Years of Relevant Experience

We are looking for an experienced Data Analytics Engineer with strong expertise in SAS Enterprise Guide (SAS EG), Advanced SAS Programming, and SAS Data Integration (SAS DI). The ideal candidate will be responsible for designing, developing, and maintaining robust data workflows and ETL processes to support business analytics and reporting needs.

Key Responsibilities

• Work extensively with SAS EG, Advanced SAS, and SAS DI to design, develop, and maintain data workflows.
• Build and optimize ETL processes using SAS DI to ensure efficient data integration and transformation.
• Manage large and complex datasets, performing data extraction, transformation, validation, and loading (ETL) activities.
• Collaborate closely with business stakeholders to understand data requirements and deliver effective SAS-based solutions.
• Ensure data accuracy, consistency, and quality across all deliverables.
• Prepare clean, structured, and reliable datasets to support reporting and analytics initiatives.
• Document data processes, workflows, and technical specifications for transparency and reusability.
• Troubleshoot and resolve issues related to SAS EG projects, Advanced SAS code, and SAS DI workflows.

Required Skills & Qualifications

• 4–6 years of hands-on experience in data analytics and data integration using SAS technologies.
• Strong command over SAS Enterprise Guide, Advanced SAS Programming, and SAS Data Integration Studio.
• Expertise in ETL design, data validation, and data quality management.
• Ability to handle large-scale datasets and optimize performance for data-intensive processes.
• Solid understanding of data warehousing concepts and analytics frameworks.
• Excellent analytical thinking, problem-solving, and communication skills.
• Proven ability to collaborate with cross-functional teams and deliver high-quality data solutions.

Why Join Us

• Work on enterprise-grade analytics solutions with leading tools and technologies.
• Opportunity to collaborate with data-driven teams across business units.
• Be part of a culture that values innovation, accuracy, and continuous learning.