EY - GDS Consulting - AI And DATA - Azure Databricks -  Manager

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

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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