Iceberg, Doris, Trino

Infosys Limited; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

Infosys Limited is seeking an experienced Data & Analytics Engineer to design and deliver lakehouse architectures, leveraging Iceberg, Doris, and Trino for scalable analytics. You will architect table layouts, optimize queries, and build robust batch and streaming pipelines with Spark.

The role requires mentoring teammates and driving best practices across the platform. The ideal candidate has 6–8 years of experience in data engineering, with strong hands-on expertise in Iceberg, Trino, Doris,

Qualifications

• Bachelor’s or Master’s degree in BTECH/MTECH/MCA/MSC or related field.
• 6-8 years of experience in data engineering or analytics platforms.
• Strong hands-on expertise with Iceberg table design, partitioning, and maintenance.
• Strong hands-on expertise with Trino for federated querying and optimization.
• Strong hands-on expertise with Doris for OLAP data modeling and performance.
• Proven experience building data pipelines using Spark in production.

Responsibilities

• Lead architecture and implementation of lakehouse analytics using Iceberg, Doris, and Trino for scalable querying and reporting.
• Design and maintain Iceberg table layouts, partitioning, schema evolution, and data lifecycle management.
• Build and optimize distributed query workflows in Trino, including tuning and resource governance.
• Develop and optimize analytical data models and ingestion patterns using Doris for OLAP workloads.
• Implement robust batch/stream processing pipelines using Spark for scalable, cost-efficient processing.
• Establish performance benchmarks, monitor SLAs, and troubleshoot production across compute/storage/query layers.
• Drive data quality, reliability, and operational excellence through automation and runbooks.
• Mentor engineers, conduct design reviews, and lead technical decision-making aligned with long-term goals.

Skills

Iceberg

Trino

Doris

Spark

Distributed data platforms

Data modeling

Query optimization

Education

Bachelor’s or Master’s in Engineering/CS/related

Tools

Iceberg

Trino

Doris

Spark

Job description

Job ID/Reference Code INFSYS-INDEED1-252715

Work Experience 6 - 8 Years

Educational Requirements

MCA,MTech,Bachelor of Engineering,BTech

Service Line

Data & Analytics Unit

Responsibilities

Key Responsibilities:

• Lead the architecture and implementation of lakehouse and analytics solutions using Iceberg, Doris, and Trino for scalable querying and reporting.
• Design and maintain Iceberg table layouts, partitioning strategies, schema evolution patterns, and data lifecycle management (compaction, snapshots, retention).
• Build and optimize distributed query workflows in Trino, including connector configuration, query tuning, resource governance, and workload management.
• Develop and optimize analytical data models and ingestion patterns leveraging Doris for high-performance OLAP workloads.
• Implement robust batch/stream processing pipelines using Spark, ensuring correctness, scalability, and cost efficiency.
• Establish performance benchmarks, monitor SLAs, and troubleshoot production issues across compute, storage, and query layers.
• Drive best practices for data quality, reliability, and operational excellence through automation, documentation, and runbooks.
• Mentor engineers, conduct design reviews, and lead technical decision-making aligned with long-term platform goals.

Minimum Qualifications

• Bachelor’s or Master’s degree in BTECH, MTECH, MCA, MSC or a related field.
• 6-8 years of experience in data engineering, analytics engineering, or building distributed data platforms.
• Strong hands-on expertise with Iceberg, including table design, partitioning, schema evolution, and maintenance operations.
• Strong hands-on expertise with Trino for federated/distributed querying, performance tuning, and operational troubleshooting.
• Strong hands-on expertise with Doris for OLAP use cases, data modeling, and query performance optimization.
• Proven experience building data pipelines using Spark in production environments.
• Solid understanding of distributed systems, query execution concepts, and data storage formats for analytics workloads.

Additional Responsibilities

Preferred Qualifications:

• Experience designing end-to-end lakehouse architectures integrating Iceberg with multiple compute engines and downstream consumers.
• Advanced expertise in query optimization techniques (statistics, partition pruning, file sizing, caching strategies) across Trino and OLAP systems.
• Experience with Spark optimization (shuffle tuning, join strategies, adaptive execution) and building reusable pipeline frameworks.
• Strong operational ownership: monitoring, alerting, incident management, and capacity planning for analytics platforms.
• Ability to lead cross-team technical initiatives, influence standards, and improve platform adoption through enablement and documentation.

Technical and Professional Requirements

Iceberg, Doris, Trino

Preferred Skills

Technology->Java->Apache->Apache Foundational->Development process generic->Big Data Analytics Process->Big Data Technology->Cloud Platform->Azure Analytics Services->Azure Data Lake