EY EY - GDS Consulting AI DATA Azure Databricks Manager 

India, Telangana, Hyderabad 

38775476

Data Engineering Lead

• Pull/ingest data from different sources, transform and stitch, and wrangle it for advanced analytics activities.
• Design, implement, and deploy data loaders to load data into the Engineering Sandbox.
• Leverage data best practices and tools and assist ML engineer in pulling, filtering, tagging, joining, parsing, and normalizing data sets for use.
• Provide input to ML engineer/cloud engineer for the design and implementation of data management and/or architecture solutions.
• 8-11years of related work experience and at least 7+ years of experience as a cloud solutions architect or equivalent in the area of data solutions designing cloud-based data architectures, data modeling, data warehousing/data lake solutions and data migration scenarios including both hybrid and pure cloud data solutions.
• At least 5+ years of hands on experience with any of the following Azure data services: Azure Synapse, Azure SQL Database, Azure Cosmos DB, Azure Data Lake, Azure Data Factory, and Azure Databricks or related
• Designing, developing, implementing, and translating business requirements and the overall organizational data strategy, including standards, principles, data sources, storage, pipelines, data flow, and data security policies.
• Strong knowledge on infrastructure components (Clusters, VMs, SQL Server, Vnet, Integrations) to support data migration deliverables on time and on budget.
• Collaborating with data engineers, data scientists, and other stakeholders to execute the data strategy.
• Communicating and defining data architecture patterns in the organization that guide the data framework.
• Support/lead data teams to develop secure, scalable, high-performance, and reliable systems to support data migration, data cleansing, and reporting.
• Other activities to support data migration/data cleansing, as needed by the project team.
• Transactional and Analytical Data Modeling expertise.
• Strong Data Governance and Data Quality principles and experience with incorporating best data quality practices in data pipelines.
• Progressive career with on-hands on Data Engineering experience.

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