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mentor data engineering teams across multiple delivery workstreams.\nDrive the development of batch, streaming and real-time data pipelines.\nLead data modeling across Silver and Gold layers, including modernization of legacy data models and source-to-target mappings.\nEstablish engineering standards covering development, testing, CI/CD, monitoring and operational support.\nProvide technical leadership across data migration, reconciliation, data quality and governance.\nReview solution designs and ensure scalability, performance, security and maintainability.\nCoordinate technical dependencies, risks and issues across engineering, architecture and migration teams.\nWork closely with business stakeholders, architects, SMEs and implementation partners.\nSupport planning, estimation and successful end-to-end delivery of the program.\nWhat We're Looking For\n10+ years' experience in data engineering, data platforms, data warehousing or related areas.\nStrong experience leading technical teams and complex enterprise data programs.\nHands-on understanding of modern Lakehouse architectures and data engineering patterns.\nStrong experience with Spark/PySpark, SQL, Kafka and Apache Iceberg.\nExperience with Cloudera Data Platform (CDP) or similar enterprise data platforms.\nStrong understanding of data modeling, ETL/ELT, data migration and data quality.\nExperience with CI/CD, automation, monitoring and production-grade data engineering.\nStrong stakeholder-management and technical leadership skills.\nGood to Have\nExperience in one or more of the following would be advantageous:\nBanking or financial services\nApache NiFi, Flink or Airflow\nCloudera ecosystem technologies\nData governance tools such as Atlas, Ranger or Informatica\nDenodo or semantic/analytics layers\nLarge-scale data migration or EDW modernization\nRegulatory or governance-driven data environments\nAI and advanced analytics 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