Data Engineer – SAS to Python migration

Key skills

What you’ll do

• The role focuses on migrating legacy SAS-based data pipelines and workflows to Python-based solutions. Responsibilities include optimizing ETL processes and collaborating with stakeholders to validate migrated datasets and ensure data quality.

What they’re looking for

• Candidates need strong data engineering skills with proficiency in Python, SAS translation, and SQL. A bachelor's degree in Computer Science or a related field is required along with experience in version control and CI/CD practices.

Job description

Role Description This full-time Data Engineer role focuses on migrating existing SAS-based data pipelines and workflows to Python-based solutions. The position is hybrid, based in Hyderabad, with the flexibility for some work from home as per project needs. Day-to-day responsibilities include analyzing legacy SAS code, designing and implementing equivalent Python data pipelines, and optimizing ETL processes for performance, reliability, and scalability. The Data Engineer will collaborate with data analysts, data scientists, and business stakeholders to validate migrated datasets, ensure data quality, and maintain documentation. The role also involves supporting data warehousing initiatives, troubleshooting production issues, and contributing to best practices for modern data engineering within Teclusion’s AI-driven ecosystem. Qualifications Strong data engineering skills, including experience building and maintaining scalable data pipelines and working with large, complex datasets. Proficiency in data modeling and data warehousing concepts for designing efficient schemas and supporting analytics and reporting needs. Hands-on experience with Extract Transform Load (ETL) processes, including orchestration, error handling, and performance tuning. Ability to perform data analytics to validate migrated data, identify data quality issues, and support business and AI use cases. Solid programming skills in Python and experience translating or re-engineering SAS code to modern data engineering frameworks. Familiarity with SQL and relational databases; exposure to cloud data platforms (e.g., AWS, Azure, GCP) is beneficial. Experience with version control (e.g., Git), CI/CD practices, and collaborative development workflows. Strong problem-solving skills, attention to detail, and ability to work effectively in a hybrid environment with cross-functional teams. Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.

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