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Strong Tier-1 brand, metro location, and specialized big-data skills create moderate competition.
Deep Databricks, PySpark and Kafka expertise makes cross-industry transfers difficult.
Explicit 13+ years and mandatory Databricks/PySpark/Kafka skills make filters highly stringent.
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Build and maintain big data platform ensuring timely delivery across multiple initiatives.
Collaborate with architects, business stakeholders, and data scientists to develop automated solutions meeting business risk and control needs.
Evaluate complex technical challenges and provide solutions, including testing, debugging, and code quality adherence.
13+ years of professional experience in data engineering with strong Spark architecture exposure.
Hands-on experience with PySpark, Spark development, Delta Lakehouse, Kafka real-time message consumption, and Unix/HDFS.
Working knowledge of Databases (SQL), BitBucket or equivalent SCM tools; experience with Kubernetes and ECS.
Experience with Databricks and S3 environments; PySpark in Hadoop and Spark environments required.
Experienced in large-scale data engineering projects involving complex data processing and automation.
Proficient in modern data architectures including Delta Lakehouse, Databricks, and real-time streaming with Kafka.
Capable of independently managing development cycle from technical problem analysis to deployment in collaborative, multi-team settings.