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)

📌 Solution Architect Cloud Solutions (Chennai)
🏢 Recognized
📍 Chennai