Sr. Data Engineer

Zensar · India

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Key Responsibilities


Required Technical Skills

Core Skills


Expected Contributions


Preferred Qualifications

Target Designation: Senior Data Engineer
Location Preference: Offshore
Primary Skills: Talend, Snowflake, Advanced SQL, Matillion, Data Pipeline Engineering, Data warehousing.

Secondary Skills: Postgress, API integration, AWS, Matillion, Azure DevOps

At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status. Role Summary We are looking for an experienced Senior Data Engineer with strong expertise in modern data engineering, data integration, and cloud-based data platforms. The resource will be responsible for diagnosing and resolving data quality and critical integration issues, implementing sustainable fixes across data pipelines, and ensuring reliable data delivery across enterprise systems.

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