Get more replies from employers
Send a job-specific resume in minutes.
Vivantify is seeking a Data Engineer with 5–7 years of experience to design and operate reliable data pipelines. The role emphasizes PostgreSQL and SQL performance optimization, data modeling, data quality, and scalable data integration for analytics and real-time consumption.
You will collaborate with data wranglers, data scientists, and development teams to deliver enterprise data assets and production-grade SQL solutions across Pan-India data ecosystems.
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.
Job Description
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.