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Tier-1 brand, mid-level generalist Data Engineer role with broad streaming and big-data requirements drives high competition.
Specialized streaming and lakehouse tech moderately limits cross-industry transferability.
Explicit 4–8 years plus mandatory Spark/Flink/Kafka/Trino/Iceberg skills create strict shortlisting filters.
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Enhance and operate big data platform technologies including Kafka-based streaming applications and data processing jobs in Apache Spark and Flink.
Manage large analytical datasets using data lake technologies like Apache Iceberg and optimize jobs for performance and cost efficiency.
Collaborate with product team to develop data and analytics pipelines and maintain high code quality through testing and reviews.
4-8 years of experience in data engineering and software development.
Proficiency in Apache Spark, Apache Flink, Kafka, and query engines like Trino or Presto.
Strong coding skills in Java/Scala, Python, or equivalent languages and strong SQL knowledge with data modeling for analytics.
Experience working with open source data ecosystem and scaling Kafka for high volume workloads.
Experienced data engineer with hands-on skills in building and tuning large-scale streaming and batch data pipelines using open source big data technologies.
Comfortable working in a fast-paced environment on both platform development and analytics data pipelines with cross-functional teams.
Familiarity with advanced data lake formats (Apache Iceberg), real-time analytics stores (Apache Pinot/Clickhouse), and orchestration tools (DolphinScheduler, Airflow) is a plus.