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    Job · 19520785

    Infosys logo

    Iceberg, Doris, Trino

    Infosys · Bengaluru · onsite · Posted 24d ago

    Undisclosed6–8 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Job DescriptionStep into a high-impact role where youll lead the design and evolution of modern analytics platforms powered by Iceberg, Doris, and Trino. Youll work at the intersection of data engineering and query performance, helping teams unlock fast, reliable insights from large-scale datasets. This role is ideal for someone who enjoys solving complex data architecture challenges, optimizing distributed systems, and guiding engineers toward clean, scalable implementations. Youll collaborate closely with data engineers, platform teams, and stakeholders to build dependable data products, improve developer experience, and ensure data is accessible, governed, and performant. If youre excited by open table formats, high-concurrency analytical workloads, and building systems that make data truly usable across an organization, this is a great place to grow and lead with purpose.
    Roles ResponsibilitiesKey Responsibilities:
  1. Lead the architecture and implementation of lakehouse and analytics solutions using Iceberg, Doris, and Trino for scalable querying and reporting.
  2. Design and maintain Iceberg table layouts, partitioning strategies, schema evolution patterns, and data lifecycle management (compaction, snapshots, retention).
  3. Build and optimize distributed query workflows in Trino, including connector configuration, query tuning, resource governance, and workload management.
  4. Develop and optimize analytical data models and ingestion patterns leveraging Doris for high-performance OLAP workloads.
  5. Implement robust batch/stream processing pipelines using Spark, ensuring correctness, scalability, and cost efficiency.
  6. Establish performance benchmarks, monitor SLAs, and troubleshoot production issues across compute, storage, and query layers.
  7. Drive best practices for data quality, reliability, and operational excellence through automation, documentation, and runbooks.
  8. Mentor engineers, conduct design reviews, and lead technical decision-making aligned with long-term platform goals.
    Minimum Qualifications:
  9. Bachelors or Masters degree in BTECH, MTECH, MCA, MSC or a related field.
  10. 68 years of experience in data engineering, analytics engineering, or building distributed data platforms.
  11. Strong hands-on expertise with Iceberg, including table design, partitioning, schema evolution, and maintenance operations.
  12. Strong hands-on expertise with Trino for federated/distributed querying, performance tuning, and operational troubleshooting.
  13. Strong hands-on expertise with Doris for OLAP use cases, data modeling, and query performance optimization.
  14. Proven experience building data pipelines using Spark in production environments.
  15. Solid understanding of distributed systems, query execution concepts, and data storage formats for analytics workloads.
    Technical RequirementIceberg, Doris, Trino
    Additional ResponsibilityPreferred Qualifications:
  16. Experience designing end-to-end lakehouse architectures integrating Iceberg with multiple compute engines and downstream consumers.
  17. Advanced expertise in query optimization techniques (statistics, partition pruning, file sizing, caching strategies) across Trino and OLAP systems.
  18. Experience with Spark optimization (shuffle tuning, join strategies, adaptive execution) and building reusable pipeline frameworks.
  19. Strong operational ownership: monitoring, alerting, incident management, and capacity planning for analytics platforms.
  20. Ability to lead cross-team technical initiatives, influence standards, and improve platform adoption through enablement and documentation.
    Educational RequirementMCA,MTech,Bachelor of Engineering,BTech
    Preferred SkillsFoundational->Development process generic->Big Data Analytics Process->Big Data,Technology->Cloud Platform->Azure Analytics Services->Azure Data Lake,Technology->Java->Apache->Apache
    Service LineData Analytics Unit
  21. Sourced from naukri

    Skills

    AutomationApachedata architecturecachingcloud platformanalytics platformsAnalyticsdata modelsConcurrencyAzure AnalyticsData EngineeringcloudArchitectureAzure Data LakeMicrosoft AzureData ModelingData PipelineBig Data

    About Infosys

    Infosys logo

    Infosys

    IT Services & Consulting

    323.6k+

    employees

    1981

    45 years old

    Bengaluru/Bangalore, Karnataka

    India

    About

    Infosys is a global leader in next-generation digital services and consulting.

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