Staff Data Engineer

• Company Visa
• No. of Openings 8
• Salary Not Disclosed
• Work Type on-site

Job Description :

• Take complete end-to-end ownership of one or more applications components.

• Responsible for the code, unit test, automation, peer review and CI/CD of one or more application components and data pipelines.

• Translate business requirements into technical solutions.

• Responsible for the design and implementation of an innovative, scalable, and distributed systems.

• Design and deploy data and pipeline management frameworks built on top of open-source components, including Hadoop, Hive, Spark, HBase, Kafka streaming and other Big Data technologies.

• Work in and promote an agile development culture focused on high quality code development and deployment to production.

• Champion Design and Coding best practices.

• This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office two days a week, Tuesdays and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.

Qualifications

- Bachelor s degree in Computer Science, or related technical discipline. With 7 or more years of software development experience in building large scale data processing platforms.
- Proficiency in engineering practices and writing high quality code, with expertise in Java
- Experience in building applications on top of Big Data open source platforms like Hadoop, Hive, Spark, HBase, Kafka streaming and other Big Data technologies.
- Experience in building applications on top Kubernetes and containers.
- Experience in handling large data volume in low latency and/or batch mode.
- Experience in building micro services with spring boot or node.js would be a plus.
- Strong team player including mentoring/growing junior engineers
- Strong on driving for results and self-motivated, strong learning mindset, with good understanding of related advanced/new technology.
- Strong verbal, written, presentation and interaction skills.
- Quick learner, self-starter, detailed and work with minimal supervision.