Data Engineer - Intermediate

What you’ll do

• Perform general application development activities, including unit testing, code deployment to development environment and technical documentation. Works on one or more projects, making contributions to unfamiliar code written by team members.

• Participates in estimation process, use case specifications, reviews of test plans and test cases, requirements, and project planning. Diagnose and resolve performance issues.

• Documents code/processes so that any other developer is able to dive in with minimal effort.

• Develop, and operate high scale applications from the backend to UI layer, focusing on operational excellence, security and scalability.

• Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.). Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset.

• Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit engineering team employing agile software development practices.

• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality.

• Able to write, debug, and troubleshoot code in mainstream open source technologies. Lead effort for Sprint deliverables, and solve problems with medium complexity

What experience you need

• Bachelor's degree or equivalent experience

• 2+ years experience working with software design and Java, Python and Javascript programming languages

• 2+ years experience with software build management tools like Maven or Gradle

• 2+ years experience with HTML, CSS and frontend/web development

• 2+ years experience with software testing, performance, and quality engineering techniques and strategies

• 2+ years experience with Cloud technology: GCP, AWS, or Azure

What Could Set You Apart:

• Knowledge or experience with Apache Beam for stream and batch data processing.

• Familiarity with big data tools and technologies like Apache Kafka, Hadoop, or Spark.

• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).

• Exposure to data visualization tools or platforms.