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Tier-1 brand, metro location, popular Big Data Engineer title and broad skill requirements increase candidate competition.
Core data engineering skills transfer broadly, but banking/markets controls domain adds moderate specificity.
Explicit 13+ years and mandatory Databricks/PySpark/Kafka experience enforce a high shortlisting filter.
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Design and deliver technical solutions for complex data processes in Markets Business Control Tech and risk functions.
Build, maintain, and ensure timely delivery on data engineering platform initiatives, enforcing code quality and testing standards.
Collaborate with architects, business stakeholders, and data scientists to meet requirements and drive automation efforts.
13+ years of professional experience in data engineering with strong exposure to Spark architecture and PySpark development.
Experience with ECS, Kubernetes, Delta Lakehouse, and Kafka for real-time message consumption is mandatory.
Working knowledge of Unix, HDFS, Python (PyArrow), SQL databases, and SCM tools like BitBucket is required.
Experience with Databricks and S3 based data architecture; knowledge of Apache Airflow is desirable.
Senior-level data engineer comfortable working with complex big data ecosystems and Spark-based architectures.
Experienced in new-age data platforms like Databricks, Delta Lake, and real-time data processing using Kafka.
Capable of operating with limited supervision and collaborating across multiple technical and business teams to deliver automated data solutions.