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Vivantify Technology Solutions India Pvt. Ltd.
in India is seeking a Data Engineer with deep PostgreSQL and SQL expertise to design, build, and maintain reliable data pipelines and enterprise data assets for analytics and real-time consumption. You will optimize PostgreSQL performance, model data, implement data quality checks, and collaborate with data scientists and developers to deliver scalable, production-grade data solutions across source and target systems.
Location: Pan India
Experience: 5–7 Years
We are looking for a Data Engineer with strong expertise in PostgreSQL and SQL to design, build, and support reliable data pipelines and enterprise data assets. The role focuses on data engineering, SQL performance optimization, data modeling, data quality, and scalable data integration for analytics and real-time consumption.
The role involves designing and maintaining data pipelines that acquire, aggregate, refine, and securely move data between source and target systems. You will develop reusable data assets that support enterprise querying, analytics, feature engineering, APIs, and ingestion processes. A key focus of the role is developing production-grade SQL and optimizing PostgreSQL performance through query tuning, execution plan analysis, indexing, partitioning, and database maintenance. You will also design logical and physical data models and establish standards for schemas, keys, constraints, naming conventions, and slowly changing dimensions. The position requires building resilient pipelines with appropriate error handling, retry mechanisms, idempotency, and reprocessing capabilities. You will collaborate with data wranglers, data scientists, and technical development teams to deliver reliable and high‑quality data solutions.
The ideal candidate should have 5–7 years of experience in data engineering with strong hands‑on expertise in PostgreSQL and advanced SQL, including database performance optimization and data modeling. The candidate should be capable of building reliable data pipelines and reusable data assets while collaborating effectively with data scientists, data wranglers, and technical development teams.