Work and enhance big data related opensource technologies.
Build and operate Kafka-based streaming applications, including ingestion, filtering, enrichment, and replication use cases.
Develop data processing jobs using Apache Spark and/or Apache Flink, following established patterns and platform guidelines.
Work with data lake technologies (Apache Iceberg) to manage large analytical datasets.
Tune jobs for performance, scalability, and cost efficiency.
Write clean, testable code and participate actively in code reviews.
Requirements
At least 4+ years of relevant experience in data engineering or software development.
Ability to work with opensource ecosystem (e.g. Apache Opensource).
Ability to write code in Java/Scala, Python, or equivalent languages.
Practical experience with Apache Spark or Apache Flink.
Experience working with Kafka (e.g. scaling of high volume workloads).
Solid SQL skills or understanding of data modelling for analytical workloads
Hands-on experience with real-time analytics stores like Apache Pinot/Clickhouse for low-latency analytical queries.
. Practical experience with query engines like Trino/Presto
Familiarity using AI Tools for debugging and development (CoPilot, Cursor, Codex).
Familiarity with data lake table formats such as Apache Iceberg.
Familiarity with data governance tools like DataHub.
Experience working with tools like DolphinScheduler or Airflow.
Experience working with Lakehouse management systems like Apache Amoro.
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Additional Information
Meet the Team
Webex Data Analytics Platform (WAP) engineering organization is responsible for developing the big data platform at Webex. The platform forms the base on which other teams, including the WAP team, develop their analytics and data pipelines.
We are looking for a hands-on Data Engineer to join a high-impact data engineering team with a focus on developing the data platform and working with the product team to develop data and analytics pipeline.
Cisco · Bratislava, Slovakia