Job#: 2063761
Job Description:
A Platform 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 develop frameworks and services 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.
Required Skills
- Programming Languages: Proficient in Java, Angular, or any JavaScript technology.
- Cloud Platforms: Experience with GCP tools like BigQuery, Dataflow, and Dataproc.
- Data Platform Technologies: Ability to design and orchestrate platform services.
- Service-Oriented Architecture (SOA) and Microservices: Strong understanding and application within a cloud data platform context.
- Full-Stack Development: Knowledge of front-end (e.g., React, Node.js) and back-end technologies.
- API Development: Experience in designing and developing RESTful APIs.
- Testing: Implement robust unit and functional tests.
- Database Management: Experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases, including columnar databases like BigQuery.
- Data Governance and Security: Understanding of data governance frameworks and implementation of RBAC, encryption, and data masking.
- CI/CD and Automation: Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform, and automation frameworks.
- Version Control: Manage code changes with GitHub.
- SDLC Best Practices: Adherence to SDLC best practices, independently managing feature design, coding, testing, and production releases.
- Problem-Solving: Strong analytical skills for troubleshooting complex data platform and microservices issues.
- Certifications (Preferred): GCP Data Engineer, GCP Professional Cloud.
Required Experience
- Minimum 5 years of experience as a Software Engineer.
Education
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. Master’s degree or equivalent experience preferred.
Additional Information
- This is a hybrid position, currently requiring 2 days a week in the office, with the possibility of increasing in the future.
EEO Employer
