Senior Data Engineer – Big Data & Streaming Platforms - Java/Scala or Python | Spark, Kafka | Flink, Iceberg / Lakehouse, Trino | 8 to 12 Years
Meet the Team
Your Impact
- 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.
Minimum Qualifications
- At least 8-12 years of experience in data engineering and software development.
- Ability to work with opensource ecosystem.
- Ability to write high-quality code in Java/Scala, Python, or equivalent languages.
- Practical experience with Apache Spark and Apache Flink.
- Practical experience with query engines like Trino/Presto.
- Experience working with Kafka and scaling for high volume workloads.
- Strong SQL skills and understanding of data modeling for analytical workloads
Preferred Qualifications
- Hands-on experience with real-time analytics stores like Apache Pinot/Clickhouse for low-latency analytical queries.
- 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.
Why Cisco?
Disclaimer
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Not included in the source posting: what you'll do, benefits.
Skills
Who can apply
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