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Lead Data Engineer (Java/Scala, Python, Spark, Kafka, SQL)

Lead Data Engineer (Java/Scala, Python, Spark, Kafka, SQL)

Cisco

12 - 17 years

17 - 22 Lacs

bengaluru

Posted:3 days ago| Platform:

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Skills Required

data engineer python data analytics software development scala airflow apache flink data engineering sql java data modeling spark use cases kafka apache spark data governance debugging big data data lake

Work Mode

Work from Office

Job Type

Full Time

Job Description

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.

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 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.

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Lead Data Engineer (Java/Scala, Python, Spark, Kafka, SQL)