Responsibilities :

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.

8â€12 years of experience in data engineering, data platform, or analytics infrastructure roles with leadership/ownership responsibilities.

Strong 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.

Additional Responsibilities:

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

Technical and Professional Requirements:

Iceberg, Doris, Trino