Data Engineer
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MidFull-time·Umowa o staż
#440712·Dodano 5 dni temu·0
Źródło: CiscoTech Stack / Keywords
Apache PinotApache IcebergFlinkSparkJavaPythonScalaGitCI/CDAI coding tools
Firma i stanowisko
Cisco's Webex Engineering Group builds collaboration technology powering products like Slido, Webex Meetings, Webex Calling, and Webex Contact Center. The team is based in Bratislava and operates a hybrid work model.
Wymagania
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
- 3+ years of professional data engineering or software engineering experience (or equivalent internship/project experience).
- Foundational knowledge of data processing frameworks (e.g., Spark, Flink) and/or distributed systems.
- Solid understanding of software development and architecture concepts with a willingness to learn new technologies quickly.
Preferred Qualifications:
- Familiarity with Apache Pinot, Apache Iceberg, Flink, or Spark.
- Familiarity with Java, Python, or Scala.
- Familiarity with Git, CI/CD pipelines, and cloud environments.
- Familiarity with AI coding tools (e.g., Codex, Cursor, Copilot).
- Eagerness to debug and resolve production data issues.
- Ability to apply creative skills to complex data problems.
- Flexible, thrives in diverse teams, and communicates clearly.
- Strong attention to detail and commitment to continuous learning and quality.
Obowiązki
- Design, implement, and maintain data pipelines for streaming and batch processing with guidance from senior team members.
- Develop and optimize data workflows using Apache Pinot, Apache Iceberg, Flink, and Spark.
- Participate in design discussions, code reviews, and testing.
- Improve data pipeline performance, reliability, and observability by resolving technical issues.
- Leverage AI coding tools (e.g., Copilot, Cursor) to accelerate productivity and learning.
- Collaborate with software engineers, product management, and data teams.
- Participate in incident resolution and learn from production issues through postmortems.
- Commit to continuous learning, data quality, and operational excellence.
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