Solution Architect Cloud Solutions

As a Solution Architect at our company, you will be responsible for architecting, designing, and scaling data-intensive, cloud-native platforms that support analytics, operational systems, and AI/ML workloads. Your deep system design skills, database knowledge, DevOps experience, and ability to build end-to-end enterprise solutions in cloud environments will be key to your success in this role. Key Responsibilities: - 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 and reliability Python Solution: - Architect and deploy Python services in tandem with ML Engineers - Handle data ingestion, transformation, and orchestration - Develop analytics, reporting, and decisioning systems - Build ML/AI pipelines and feature processing - Utilize Python frameworks and tools such as FastAPI, Flask, Pandas, PySpark, and Dagster Java-Based Data Services: - Design and govern Java backend and data services - Implement REST/gRPC APIs and high-throughput data access services - Develop streaming and event-driven services - Work with technologies like 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 - Analyze and tune SQL queries, query plans, indexes, partitions, joins, and materialized views - Optimize performance across relational databases, cloud-native databases, and data warehouses - Lead efforts in schema design, normalization/denormalization tradeoffs, indexing strategies, partitioning, query refactoring, workload tuning, and database cost and performance optimization Data & Streaming Platforms: - Architect solutions using data lakes, lakehouses, and streaming platforms such as S3, ADLS, GCS, Delta, Iceberg, Hudi, Kafka, Flink, and Spark Structured Streaming Join us in creating cutting-edge solutions and driving innovation in the world of cloud-native platforms and data-intensive systems. As a Solution Architect at our company, you will be responsible for architecting, designing, and scaling data-intensive, cloud-native platforms that support analytics, operational systems, and AI/ML workloads. Your deep system design skills, database knowledge, DevOps experience, and ability to build end-to-end enterprise solutions in cloud environments will be key to your success in this role. Key Responsibilities: - 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 and reliability Python Solution: - Architect and deploy Python services in tandem with ML Engineers - Handle data ingestion, transformation, and orchestration - Develop analytics, reporting, and decisioning systems - Build ML/AI pipelines and feature processing - Utilize Python frameworks and tools such as FastAPI, Flask, Pandas, PySpark, and Dagster Java-Based Data Services: - Design and govern Java backend and data services - Implement REST/gRPC APIs and high-throughput data access services - Develop streaming and event-driven services - Work with technologies like 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 - Analyze and tune SQL queries, query plans, indexes, partitions, joins, and materialized views - Optimize performance across relational databases, cloud-native databases, and data warehouses - Lead efforts in schema design, normalization/denormalization tradeoffs, indexing strategies, partitioning, query refactoring, workload tuning, and database cost and performance optimization Data & Streaming Platforms: - Architect solutions using data lakes, lakehouses, and streaming platforms such as S3, ADLS, GCS, Delta, Iceberg, Hudi, Kafka, Flink, and Spark Structured Streaming Join us in creating cutting-edge solutions and driving innovation in the world of cloud-native platforms and data-intensive systems.