Senior Microservices Backend Engineer

• Design and development of API services for managing Databricks resources, services & features and to support data governance applications to manage security of data assets following the standards
• Design and development of enterprise-level re-usable components, frameworks and services to enable data engineers
• Serve as a Lead Engineer for technical implementation of projects including planning, architecture, design, development, testing, and deployment following agile methodologies
• Collaborate with Lead Architect, Business SMEs, and Data Engineers to design cloud data solutions
• Proactively work on challenging data integration problems by implementing efficient ETL patterns, frameworks for structured and unstructured data
• Automate and optimize data pipeline and framework for easier and efficient development process
• Overall management of the Enterprise Data Fabric/Lake on AWS environment to ensure that the service delivery is efficient and business SLAs around uptime, performance and capacity are met
• Help define guidelines, standards, strategies, security policies and change management policies to support the Enterprise Data Fabric/Lake
• Partner with project managers, architects, business analysts, and engineers to provide technical leadership on cloud platforms (AWS, Databricks), ensuring the design and delivery of robust, scalable, and maintainable Data Lake and Big Data solutions.
• Experience developing in an Agile development environment and ceremonies
• Familiarity with code versioning using GITLAB, and code deployment tools
• Mentor junior engineers and team members

• Doctorate degree / Master's degree / Bachelor's degree and 8 to 13 years in Computer Science or Engineering
• Proficiency in Python-based microservices development and deployment.
• Proven experience with microservices design patterns, distributed systems, and API lifecycle management.
• Experience with containerization (Docker) and orchestration platforms (Kubernetes/EKS).
• Proficiency with SQL and data modeling for scalable systems.
• Familiarity with CI/CD pipelines, Git-based version control (GitLab/GitHub), and automated testing.
• Experience leading technical teams/projects, including architecture reviews, code reviews, and mentoring.
• Hands-on experience with AWS services (EKS, EC2, S3, RDS, SQS).
• Strong problem-solving skills and ability to design for scalability, security, and resilience.

• Experience building APIs and services for provisioning and managing AWS Databricks environments.
• Knowledge of Databricks SDK and REST APIs for managing workspaces, clusters, jobs, users, and permissions.
• Experience developing self-service portals using front-end frameworks like React.js.
• Demonstrated ability to build enterprise-grade, performance-optimized data pipelines in Databricks using Python and PySpark, following best practices and standards.
• Familiarity with building AI/ML solutions using Databricks-native features.
• Experience working with SQL/NoSQL databases and vector databases for large language model (LLM) applications.
• Exposure to model fine-tuning and timely engineering practices.
• Good communication skills to effectively present technical information to leadership and respond to collaborator inquiries.
• Certifications (preferred but not required): AWS Certified Data Engineer
• Databricks Certification
• SAFe Agile Certification

Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.