Senior Data Platform Engineer

The Senior Engineer, Data Platform Engineering, designs, develops and maintains digital technology infrastructure to support information technology applications and services. With minimal supervision, this person collaborates with cross functional teams to define, design and implement new features to meet user needs and business goals, and upgrade existing platforms to improve performance and functionality through writing clean, efficient and scalable code and troubleshooting and debugging complex issues. This job also participates in code reviews to maintain high code quality and share knowledge with platform engineering team members.  

·       Software Development: Designs and develops high quality software solutions by writing clean, maintainable and efficient codes.

·       Automation: Leads the application of internal software deployment platform, continuous integration or continuous delivery pipeline and twelve factor development methodology to automate the deployment process, ensuring smooth and reliable releases.

·       Collaboration: Partners with cross functional team of product managers, designers and other engineers to gather complex requirements and deliver solutions that meet business needs.

·       Testing & Debugging: Writes and maintains complex unit tests and integration tests and performs debugging to maintain the quality and performance of the software, applying test driven development as needed.

·       Continuous Improvement: Recommends options for improving the software development and deployment processes and implements the approved standards to improve efficiency and reliability.

·       Documentation: Creates and maintains comprehensive documentation for complex software applications, deployment processes and system configurations.

·       Technical Support: Provides technical support and troubleshooting for complex issues with deployed applications to ensure minimal downtime and fast resolution.

·       Reliability & Professionalism: Delivers across multiple teams/programs with reliable forecasts; manages risks/constraints; maintains operational health metrics and on‑call reliability.

·       Design & Solutioning: Designs and builds moderately complex data products that meet functional and non‑functional requirements. Ensures solutions are scalable, cost‑aware, and observable.

·       Minimum requirement of 5 years of relevant work experience out of a total of 8 plus years in the industry. Typically reflects 10 years or more of IT experience.

·       Proficient in Python frameworks for data processing, API integration, and working with various data formats used in big data and streaming systems.

·       Design and operate secure data platforms and pipelines on AWS, leveraging core services such as IAM, S3, Lake Formation, Glue, Lambda, RDS and CloudWatch.

·       Strong command of SQL and relational databases, supporting data-driven applications and analytics.

·       Implement and manage fine‑grained access controls for data assets, including role-based and attribute-based access patterns.

·       Build and maintain metadata capabilities (cataloging, classification, lineage, and tagging) to support governance, discoverability, and compliance. Experience with cataloging and discovery tools.

·       Embed security-by-design across data ingestion, storage, and consumption layers, including encryption, secrets management, network controls, and audit logging.

·       Align platform implementations with control frameworks such as NIST, translating policy requirements into enforceable technical controls and supporting audit readiness.

·       Collaborate with data, platform, and security teams to enable scalable, self-service data access while maintaining strong governance standards.