Job Description

Job Summary

software Engineer is a versatile developer with expertise in Java or Python and a strong foundation in cloud platforms to build and manage applications at scale. Generally, platform engineers fall into two categories: backend engineers, who design and implement microservices with robust APIs, and full-stack engineers, who deliver native UI/UX solutions, and ability to develop frameworks and service to enable an enterprise data platform. With a solid understanding of the SDLC and hands-on experience in Git and CI/CD, platform engineers can independently design, code, test, and release features to production efficiently. Key Responsibilities: • 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.

Key Responsibilities

1. To be responsible for providing technical guidance / solutions ;define, advocate, and implement best practices and coding standards for the team.
2. To develop and guide the team members in enhancing their technical capabilities and increasing productivity
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To prepare and submit status reports for minimizing exposure and risks on the project or closure of escalations.

Skill Requirements

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Other Requirements

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