Key Responsibilities

- Lead architecture and implementation of lakehouse solutions using Iceberg for table management, governance, and scalable storage patterns.
- Design and optimize distributed query workloads using Trino, including catalog configuration, connector strategy, and query performance tuning.
- Build and operate high-performance analytics serving layers using Doris, focusing on ingestion patterns, schema design, and workload isolation.
- Drive end-to-end data pipeline execution leveraging Spark for batch processing, transformations, and data quality enforcement.
- Establish standards for data modeling, partitioning, compaction, file sizing, and lifecycle management to improve cost and performance.
- Own production readiness: monitoring, alerting, incident response, root-cause analysis, and continuous performance improvements across the stack.
- Collaborate with stakeholders to translate analytical needs into scalable technical designs, delivery plans, and measurable outcomes.
- Mentor engineers, conduct design/code reviews, and guide best practices for reliability, maintainability, and secure data access.

Minimum

Qualifications:

- BTECH, MTECH, MCA, or MSC in Computer Science, Engineering, or a related field.
- 8–12 years of experience in data engineering, data platform,



or analytics infrastructure roles with leadership/ownership responsibilities.
- Robust hands-on expertise with Iceberg, Doris, and Trino in production environments, including performance tuning and operational support.
- Strong experience with Spark for scalable data processing and pipeline development.
- Solid understanding of distributed systems, data storage formats, query optimization, and production troubleshooting practices.

Preferred

Qualifications:

- Proven experience designing lakehouse architectures, including table layout strategies, compaction approaches, and multi-engine interoperability.
- Advanced Trino optimization experience (query plans, statistics, resource groups, connector tuning) for high concurrency and large datasets.
- Strong Doris operational expertise including ingestion optimization, indexing strategy, and workload management for BI/analytics use cases.
- Experience strengthening platform reliability through observability, capacity planning, and performance benchmarking.
- Ability to lead cross-team technical initiatives, influence architecture decisions, and communicate trade-offs clearly to technical and non-technical stakeholders

📌 Iceberg, Doris, Trino (Bengaluru)
🏢 Infosys
📍 Bengaluru