Schwab's ODX organization is looking to build the next-generation analytics platform for a leading financial firm with over $10 trillion in assets under management. They need to manage over 4 petabytes of data and are seeking an individual with a passion for data and software engineering specializing in data to join their Data Exchange team.
Requirements
- Minimum 7 years of hands-on development experience using parallel processing databases like Teradata, Google Big Query.
- Must have 5+ years’ experience in Java Spring boot, and preferably Google Cloud Platform, and Informatica IICS
- Must have 2+ years’ experience in developing front-end applications using React.
- Experience in data streaming technologies like Kafka, RabbitMQ
- Experience with all aspects of data systems, including database design, ETL, aggregation strategy, performance optimization.
- Experience setting best practices for building and designing code and strong Java & SQL experience to develop, tune, and debug complex applications.
- Hands-on experience with programming language Java/Python/Spark
Responsibilities
- Design, develop, and maintain scalable data streaming pipelines using Java, Spring, and GCP native services such as Pub/Sub, Dataflow, or alternatives like Kafka and RabbitMQ.
- Develop and unit test high-quality, maintainable code; partner with QA to ensure comprehensive test coverage and zero-defect production releases.
- Design, develop, and manage front-end self-service portal using React.
- Build reliable batch ingestion jobs to integrate HR data from multiple upstream sources into the Operational Data Exchange (ODX) database.
- Streamline, simplify, and performance-tune batch and streaming data loads to improve throughput and minimize latency.
- Collaborate closely with business stakeholders and upstream application teams to understand requirements, align on data contracts, and build trusted relationships.
- Work with Production Support and Platform Engineering teams to triage and resolve production issues promptly, while ensuring data security and platform reliability.
Other
- Follow agile and release management best practices to ensure smooth deployments and prevent production install failures.
- Stay current with evolving technologies and trends; continuously learn and apply modern patterns for data engineering and streaming.
- Communicate effectively across technical and non-technical audiences; demonstrate ownership, adaptability, and a collaborative mindset.
- Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.
