DE&A - Senior Data Engineer (CDAI)
Zensar Technologies (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 22–35 LPA
Posted 1d ago
Reach people at Zensar Technologies
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Zensar Technologies you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and optimize enterprise-scale data pipelines and data architecture focused on performance, scalability, and AI agent consumption.
- Specialize in distributed SQL systems like Starburst/Trino for query optimization, materialized views, and tuning data products for low-latency, high-concurrency AI usage.
- Lead development and migration of complex SQL transformations to distributed frameworks such as Apache Spark (Scala/PySpark) to enhance data curation speed and efficiency.
Minimum Requirements
- Strong hands-on experience with distributed SQL technologies like Starburst/Trino including query optimization and materialized views.
- Experience in Apache Spark development with Scala and/or Python/PySpark for distributed data processing.
- Proficient with RDBMS and lakehouse architectures, preferably Apache Iceberg, including table design and data lifecycle management.
- Work Experience Required: Not explicitly mentioned in the JD
Ideal Candidate Profile
- Demonstrated ability to optimize and redesign data workflows using a blend of SQL, Spark, and other modern processing frameworks.
- Deep knowledge of data storage optimization strategies (partitioning, indexing, file formats) to enhance query performance and cost efficiency.
- Experience implementing software engineering best practices such as CI/CD, automated testing, and production support in data platforms.