Data Platform Engineer

The Engineer, Data Platform Engineering, partners with senior engineers to design, develops and maintains digital technology infrastructure to support information technology applications and services. With limited supervision, this person collaborates with cross functional teams to 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 person 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 other engineers and Architects to gather complex requirements, break it down 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.

·       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 predictably without follow‑up; estimates accurately; manages dependencies and keeps team SLAs/commitments green.

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

·       Quick learner and flexible to move across technology stacks to meet varying business needs of DT&D organization.

·       Minimum requirement of 2 years of relevant work experience out of a total of 4 plus years in the industry. Typically reflects 5 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.

·       Very good hands-on experience with Terraform and scripted automations. Experience building AND operating DevOps pipelines in AWS codepipeline / Jenkins for application deployment.

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

·       Good command of SQL and working knowledge of relational database administration in AWS.