Data Platform Architect - Lakehouse and Analytics Infrastructure

Infosys; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Infosys in Bengaluru is seeking a senior data platform architect to lead lakehouse design and governance using Iceberg, with a focus on scalable storage and multi-engine interoperability.

You will optimize Trino workloads for high concurrency, build Doris-based analytics layers, and drive end-to-end Spark-based data pipelines, ensuring reliability and performance.

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.
• 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.

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.

Skills

Lakehouse architecture

Trino optimization

Doris operations

Observability & capacity planning

Leading cross-team initiatives

Education

BTECH/MTECH/MCA/MSC in CS/Engineering

Tools

Iceberg

Trino

Doris

Spark

Job description

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

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.


• 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.