Data Engineering Manager

Job Responsibility : 1. Data Engineering and Data Warehouse Architecture: - Collaborate with stakeholders to define the business layer and data transformation layer of the data model, ensuring easy access to data dimensions and schemas. - Review the existing data engineering architecture and recommend improvements as needed. - Ensure the architecture of the product or solution is scalable and suitable for the GDP layer. Data Engineering Governance Solution Design: - Lead the design, specification, and selection of data solutions, focusing on functionality, data, security, integration, infrastructure, and performance. - Possess a strong understanding of Big Data components and Data Warehousing concepts, particularly in Azure Databricks, Azure Data Factory, SQL, and NoSQL technologies like Snowflake. - Analyze requirements and develop appropriate architectural solutions, including detailed design documentation. Business Partnering: - Have a solid understanding of data quality, metadata management, and master data management concepts. - Be knowledgeable about privacy laws and regulations, particularly concerning first-party data. - Understand financial laws related to data security, compliance, and other relevant regulations. - Ability to work effectively under tight deadlines and in a dynamic work environment. EXPERIENCE • 20 to 15+ years of Experience with one or more Big Data or Analytics Products and Services: Hadoop, Spark, Hive, Azure Databricks 12+ years in Data Warehouse 12+ years in Data Modelling 10+ years in BI project management Good knowledge of EPR, B2B , D2C and Sales systems and reporting. Exposure to AI and Machine Learning. Data Engineering – Data Factory / Databricks (PySpark, SQL)/ Pandas / Numpy / MXNet / TensorFlow Classified as Internal Deployment - Azure Data Factory / Apache Airflow AI & ML – CNN, Federated Learning, Poisoning attacks and defenses Programming Languages – Python / SQL / Java