Solution Architect Cloud Solutions (Chennai)

• Solution Architect Cloud Solutions (Chennai)
• Company: Recognized
• Job Location: Chennai, Tamil Nadu, India
• Employment Type: Full-time
• Role Summary:

We are seeking a Solution Architect with expertise in Python and Java-based services, and advanced database/SQL and data pipeline performance optimization. This role will architect, design, and scale data-intensive, cloud-native platforms supporting analytics, operational systems, and AI/ML workloads. The ideal candidate combines deep system design skills, database knowledge, DevOps, and the ability to build end to end enterprise solutions in cloud environments.

• Key Responsibilities
• Cloud Architecture & Platform Design
• Own end-to-end cloud solution architecture for data-driven platforms
• Design scalable, fault-tolerant, cloud-native systems using Python and Java
• Define architectural standards for microservices, data access layers, and APIs
• Ensure solutions meet performance, security, cost, and compliance requirements
• Continuously monitor and incrementally evolve system performance, reliability
• Python Solution
• Architect and deploy Python services in tandem with ML Engineers:
• Data ingestion, transformation, and orchestration
• Analytics, reporting, and decisioning systems
• ML/AI pipelines and feature processing
• Python frameworks and tools such as:
• FastAPI / Flask
• Pandas, PySpark, Dagster
• Java-Based Data Services
• Design and govern Java backend and data services, including:
• REST / gRPC APIs
• High-throughput data access services
• Streaming and event-driven services
• Work with technologies such as:
• Spring Boot / Spring Cloud
• Connection pooling, caching, and resilience patterns
• Database Architecture & SQL Optimization
• Design and optimize database architectures for both OLTP and OLAP workloads
• Deeply analyze and tune SQL queries:
• Query plans, indexes, partitions, joins, and materialized views
• Locking, concurrency, and transaction isolation
• Optimize performance across:
• Relational databases (Postgres, MySQL, SQL Server, Oracle)
• Cloud-native databases (Aurora, Cloud SQL, Azure SQL)
• Data warehouses (Snowflake, BigQuery, Synapse)
• Lead efforts in:
• Schema design and normalization/denormalization tradeoffs
• Indexing strategies and partitioning
• Query refactoring and workload tuning
• Database cost and performance optimization
• Data & Streaming Platforms
• Architect solutions using:
• Data lakes and lakehouses (S3/ADLS/GCS, Delta, Iceberg, Hudi)
• Streaming platforms (Kafka, Flink, Spark Structured Streaming) .