Join EY to build a career that's as unique as you are, leveraging global scale, support, and an inclusive culture. As a Manager in Data Engineering, you will be crucial to our Data and Analytics team, delivering cutting-edge solutions across data management, visualization, business analytics, and automation for diverse client projects and industries.

This role is instrumental in conceptualizing, designing, developing, and maintaining sophisticated technology solutions that address complex business challenges for our clients. You will collaborate closely with technical architects, subject matter experts, and other solution architects, acting as a key liaison for onshore teams. Your expertise will drive the evolution of modern data warehousing and data integration, utilizing advanced tools for both on-premise and cloud environments.

You will be responsible for evaluating and selecting appropriate data warehousing tools for business intelligence, data management, and administration across on-premise and cloud engagements. A significant part of your role will involve designing, developing, and testing ETL workflows, creating detailed design documentation including data mappings, technical specifications, and test cases. You'll provide technical leadership to data warehouse and business intelligence developers, coordinate on data governance and cloud implementation strategies, and ensure adherence to ETL/Data Warehouse development best practices.

Key responsibilities include managing data orchestration, ingestion, ETL, and reporting architecture for both on-premise and cloud platforms (MS Azure/AWS/GCP), and assisting teams with performance tuning for ETL and database processes. You will also oversee the creation of design specifications, documentation, and development of data migration mappings and transformations for modern data warehouse setups and data mart creation, defining robust ETL processes for structured and unstructured data to enable self-serve analytics reporting.

We seek a seasoned professional with a minimum of 9 years of total experience, including at least 6 years in Data Warehousing or Business Intelligence. You should possess solid hands-on experience (6+ years) in creating and implementing data warehouses, alongside strong knowledge of data architecture for staging and reporting schemas, data models, and cutover strategies.

Essential qualifications include architecture design and implementation experience with medium to complex on-premise to cloud migrations, preferably with AWS, Azure, or GCP. A minimum of 3 years of experience with Azure database offerings (Relational, NoSQL, Data Warehouse) and 2+ years of hands-on experience with Azure services like Data Factory, Kafka, Data Explorer, Storage, Data Lake, Synapse Analytics, Analysis Services, and Databricks is required. Furthermore, at least 3 years of hands-on database design, modelling, and integration experience with relational data sources (SQL Server, Oracle/MySQL, Azure SQL, Azure Synapse) is a must. Knowledge of BI reporting tools such as Power BI, Tableau, or others is also expected.