Platform Software Engineer

We are seeking a highly motivated and analytical Cost Optimization Engineer to join our Data Platform team. In this role, you will be responsible for identifying, analyzing, and implementing cost-saving strategies across our data platform, which is hosted in GCP. You will work closely with engineering, operations, and architecture teams to understand resource utilization, identify inefficiencies, and develop solutions to optimize cloud spending. A strong understanding and experience of any major cloud platforms like AWS, Azure, or GCP is essential, as you will be analyzing cloud billing data, recommending infrastructure changes, automating cost management processes, and ensuring adherence to cloud cost optimization best practices. Excellent problem-solving skills are crucial, as you will be tackling complex challenges related to cloud resource allocation and cost management. Your goal will be to maximize the value of our cloud investment while maintaining the performance, reliability, and security of our Data Platform.

• Design and Build Data Pipelines: Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on GCP.
• Service-Oriented Architecture (SOA) and Microservices: Design and implement SOA and microservices-based architectures to ensure modular, flexible, and maintainable data solutions.
• Full-Stack Integration: Leverage your full-stack expertise to contribute to the seamless integration of front-end and back-end components, ensuring robust data access and UI-driven data exploration.
• Data Ingestion and Integration: Lead the ingestion and integration of data from various sources into the data platform, ensuring data is standardized and optimized for analytics.
• GCP Data Solutions: Utilize GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that meet business needs.
• Data Governance and Security: Implement and manage data governance, access controls, and security best practices while leveraging GCP’s native row- and column-level security features.
• Performance Optimization: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions.
• Collaboration and Best Practices: Work closely with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering.
• Automation and Reliability: Automate data platform processes to enhance reliability, reduce manual intervention, and improve operational efficiency.

• Education:
  • Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. Master’s degree or equivalent experience preferred.
• Experience: 
  • Minimum 7 years of experience as a Software Engineer
  • Technical Skills: Proficient in Java, angular or any javascript technology with experience in designing and deploying cloud-based data pipelines and microservices using GCP tools like BigQuery, Dataflow, and Dataproc.
  • Ability to leverage best in-class data platform technologies to deliver platform features, and design & orchestrate platform services to deliver data platform capabilities.
  • Service-Oriented Architecture and Microservices: Strong understanding of SOA, microservices, and their application within a cloud data platform context. Develop robust, scalable services using Java Spring Boot, Python, Angular, and GCP technologies.
  • Full-Stack Development: Knowledge of front-end and back-end technologies, enabling collaboration on data access and visualization layers (e.g., React, Node.js).
  • Design and develop RESTful APIs for seamless integration across platform services.
  • Implement robust unit and functional tests to maintain high standards of test coverage and quality.
  • Database Management: Experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases, as well as columnar databases like BigQuery.
  • Must possess excellent SQL skills, including query optimization and data manipulation. 
  • Data Governance and Security: Understanding of data governance frameworks and implementing RBAC, encryption, and data masking in cloud environments.
  • CI/CD and Automation: Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform, and automation frameworks.
  • Manage code changes with GitHub and troubleshoot and resolve application defects efficiently.
  • Ensure adher