Data Engineer

24 hours ago

Anywhere in IndiaMultiple Locations Techno Wise Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Data Engineer (SAS DQ Conversion)

Location : PAN INDIA (Preferred Hyderabad) - Hybrid

Experience : 4+ Years

About the Role :

We are seeking a motivated and detail-oriented Data Engineer to join our team. The ideal candidate will have hands-on experience with SQL, particularly translating between different SQL dialects, and a strong background or familiarity with SAS Data Quality (DQ) conversion. This role offers an excellent opportunity to work with diverse data environments and develop robust ETL pipelines that support critical business insights.

Key Responsibilities :


- Perform SAS Data Quality (DQ) conversion tasks to modernize and optimize legacy data processes.

- Write, optimize, and translate complex SQL queries across multiple SQL dialects, with an emphasis on Teradata and SAS SQL.

- Collaborate with data architects, analysts, and business stakeholders to understand data requirements and deliver reliable data pipelines.

- Assist in data integration, transformation, and migration efforts across platforms.

- Monitor and troubleshoot ETL jobs and data workflows to ensure data accuracy and reliability.

- Participate in code reviews, testing, and documentation to maintain high-quality standards.

- Support data governance and quality initiatives as part of the data engineering team.

Must-Have Skills :


- Proficient in SQL with practical experience translating between two or more SQL dialects.

- Experience with SAS Data Quality (DQ) tools and/or SAS data processing.

- Working knowledge of Teradata SQL dialect preferred.

- Understanding of ETL concepts and data pipeline development.

- Strong problem-solving skills and attention to detail.

- Ability to work collaboratively in a team and communicate effectively with technical and non-technical stakeholders.

Good-to-Have Skills :


- Prior experience in data warehousing and large-scale data environments.

- Familiarity with other SQL dialects such as PostgreSQL, MySQL, or Microsoft SQL Server.

- Basic knowledge of Python or other scripting languages used for data engineering.

- Exposure to cloud platforms (AWS) and cloud-based data services.

- Understanding of data governance, data quality frameworks, and best practices.

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