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. 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.
Senior Data Engineer
Location
India
Posted
3 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Engineer
Zensar
Role Description We are looking for a Senior Data Engineer to drive the development of a scalable, enterprise-wide data platform supporting both batch and real-time data processing. The role focuses on building a modern data ecosystem using Snowflake, DBT, AWS Glue, and Amazon Kinesis, enabling high-quality, governed, and performance-optimized data for enterprise consumption. Key Responsibilities - Architect and implement a modern data platform leveraging medallion architecture (Raw, Silver, Gold layers) on Snowflake and DBT. - Develop and manage batch ingestion pipelines using AWS Glue and real-time streaming pipelines using Amazon Kinesis. - Design scalable data models and transformation logic using DBT to support enterprise analytics and reporting needs. - Lead data pipeline optimization initiatives focusing on performance, scalability, and cost efficiency. - Ensure data quality, consistency, and governance through validation frameworks and monitoring mechanisms. - Support report rationalization initiatives by streamlining data layers and reducing redundancy. - Collaborate with cross-functional teams to translate business requirements into robust data engineering solutions. Qualifications - Strong hands-on experience with Snowflake (data warehousing, performance tuning). - DBT (data transformation, modelling, testing). - AWS Glue (batch ETL pipelines). - Amazon Kinesis (real-time data streaming). - Advanced proficiency in SQL and data modelling (dimensional and normalized). - Experience implementing Raw/Silver/Gold data architectures. - Strong programming skills in Python/Scala. - Expertise in pipeline performance tuning and cost optimization. - Insurance domain background preferred. Requirements - 6–10+ years in Data Engineering / Data Platform Development. - Proven experience building large-scale, cloud-based data platforms. Success Measures - High-performing, scalable, and reliable data pipelines. - Reduced data latency across batch and real-time workloads. - Improved data quality and governance standards. - Measurable cost and performance optimization in data platform operations. Why This Role - Opportunity to build a next-generation enterprise data platform. - Work on hybrid real-time and batch architectures at scale. - Drive data modernization and optimization initiatives.
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• Work with one of our U.S.-based clients. • Develop and implement data pipelines using PySpark. • Collaborate with cross-functional teams including machine learning engineers, software developers, analytics engineers, and product managers. • Translate business requirements into highly available data solutions. • Maintain and improve existing data pipelines and systems.
• Design, develop, and maintain robust ELT/ETL pipelines • Build and optimize data models in cloud-based data warehouses • Implement and manage orchestration frameworks • Develop streaming and real-time data pipelines • Architect and provision cloud data infrastructure on GCP • Ensure all data systems comply with HIPAA, HITECH, and applicable state privacy regulations • Implement data quality frameworks • Mentor junior data engineers
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