Join EY's Data and Analytics team as an Associate Manager, Data Engineering, and contribute to building a better working world. This role is crucial for supporting cloud and on-prem platform analytics and data engineering projects. You will conceptualize, design, develop, deploy, and maintain complex technology solutions that address client business challenges. Collaborate closely with technical architects, subject matter experts, and other solution architects in this onshore-facing position.

Your expertise will be vital in evolving modern data warehousing solutions and data integration frameworks, utilizing cutting-edge tools for both on-prem and cloud environments. This includes creating design specifications, documentation, and developing data migration mappings and transformations for data warehouse setups. You will also define robust ETL processes to manage structured and unstructured data, enabling self-serve capabilities for impactful decision analytics reporting.

Key responsibilities include evaluating and selecting data warehousing tools for business intelligence and data management across on-prem and cloud engagements. You will leverage strong working knowledge of the technology stack, including ETL, ELT, data analysis, metadata, data quality, and audit processes. Design, develop, and test ETL workflows using GUI-driven tools, and create comprehensive design documentation such as data mapping and technical specifications. Provide technical guidance to data warehouse and business intelligence developers, and coordinate with other technology users on data governance, harvesting, cloud implementation, privacy, and security.

Adhere to ETL/Data Warehouse development best practices, and manage data orchestration, ingestion, ETL, and reporting architecture for both on-prem and cloud platforms (MS Azure/AWS/GCP). You will also assist the team with performance tuning for ETL and database processes, ensuring optimal system performance and efficiency.

We seek individuals with a minimum of 7 years of total experience, including at least 3 years in Data Warehousing or Business Intelligence. A solid foundation of 3+ years in professional experience with data warehouse creation, implementation, and enhancement is essential. You should possess strong knowledge of data architecture for staging and reporting schemas, data models, and cutover strategies using industry-standard tools.

Demonstrate architecture design and implementation experience with medium to complex on-prem to cloud migrations, preferably on AWS/Azure/GCP. A minimum of 3 years of experience with Azure database offerings (Relational, NoSQL, Data Warehouse) and 2+ years with Azure services like Azure Data Factory, Kafka, Azure Data Explorer, and Azure Synapse Analytics is required. Additionally, possess at least 3 years of hands-on database design, modeling, and integration experience with relational data sources, along with 3 years of programming experience, preferably in Python.

Familiarity with business intelligence reporting tools (e.g., Power BI, Tableau) and strong creative instincts for data analysis and visualization are crucial. A curious mindset for learning business methodologies, data models, and user personas, coupled with a strong understanding of BI and DWH best practices, analysis, visualization, and latest trends, is expected. Experience with the software development life cycle (SDLC) and a willingness to mentor team members are also key attributes. Excellent written and verbal communication skills, along with strong thoughtfulness and problem-solving skills, are necessary for success in this role.