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