SaT - DnA - Senior Analyst (Noida, ...

Join EY's Data and Analytics team as a Senior Analyst - Data Engineering in Noida, India. This role supports cloud and on-prem platform analytics and data engineering projects, focusing on conceptualizing, designing, developing, deploying, and maintaining complex technology solutions to solve client business problems. You will work with technical architects, product and business subject matter experts, and other solution architects. This instrumental role involves designing, developing, and evolving modern data warehousing solutions and data integration build-outs using cutting-edge tools for both on-prem and cloud architectures. Responsibilities include creating design specifications, documentation, developing data migration mappings and transformations, and defining robust ETL processes for structured and unstructured data to enable self-serve capabilities and impactful decision analytics reporting.

As a Data Architect & Engineer at EY, you will design, build, and operate scalable on-premises or cloud data architecture and modeling solutions that support the entire data asset lifecycle, including storage, integration, management, validation, and security. You will also build and operate data integration solutions to optimize data flows by consolidating disparate data into a single solution, and collaborate with cross-functional teams to deliver business value through analytics solutions.

Key Responsibilities:

• Evaluate and select data warehousing tools for business intelligence, data population, management, metadata management, and warehouse administration (on-prem and cloud).
• Demonstrate strong working knowledge across ETL, ELT, data analysis, metadata, data quality, audit, and design.
• Design, develop, and test workflows in ETL tool environments.
• Produce design documentation including data mapping, technical specifications, production support, data dictionaries, and test cases.
• Provide technical guidance to data warehouse and business intelligence developers.
• Coordinate with other technology users on data governance, harvesting, cloud implementation strategy, privacy, and security.
• Adhere to ETL/Data Warehouse development best practices.
• Manage data orchestration, ingestion, ETL, and reporting architecture for on-prem and cloud platforms (MS Azure/AWS/GCP).
• Assist with performance tuning for ETL and database processes.

Skills and Attributes for Success:

• Minimum 4 years of experience in Data Warehousing/Business Intelligence.
• Minimum 3+ years of professional experience in creating and implementing data warehouses and enhancements.
• Strong knowledge of data architecture for staging and reporting schemas, data models, and cutover strategies.
• Architecture design and implementation experience with on-prem to cloud migrations using major cloud platforms (AWS/Azure/GCP).
• Minimum 3+ years of experience in Azure database offerings (Relational, NoSQL, Datawarehouse).
• 2+ years of hands-on experience with Azure services such as Azure Data Factory, Kafka, Azure Data Explorer, Storage, Azure Data Lake, Azure Synapse Analytics, Azure Analysis Services, and Databricks.
• Minimum 3 years of hands-on experience with database design, modelling, and integration with relational data sources (SQL Server, Oracle/MySQL, Azure SQL, Azure Synapse).
• Knowledge and experience with business intelligence reporting tools (Power BI, Alteryx, OBIEE, Business Objects, Cognos, Tableau, MicroStrategy, SSAS Cubes).
• Strong analytical and visualization instincts.
• Curiosity to learn business methodologies, data models, and user personas.
• Strong understanding of BI and DWH best practices, analysis, visualization, and emerging trends.
• Experience with the software development lifecycle (SDLC) and product development rules.
• Thoughtfulness, technical, and problem-solving skills.
• Excellent written and verbal communication skills.

Qualifications:

• Bachelor's or equivalent degree in computer science or a related field; advanced degree or equivalent business experience preferred.
• Fact-steered with excellent attention to detail.
• Hands-on experience with data engineering tasks, building analytical data records, and manipulating/analyzing large data volumes.
• Minimum 4-6 years of relevant work experience in a Big 4 or technology/consulting setup.

Ideally, you’ll also have:

• Strategic, end-to-end thinking with a result-oriented mindset.
• Ability to build rapport and client trust.
• Willingness to travel extensively and work on client sites.

EY GDS is a dynamic and global delivery network focused on supporting EY's growth strategy across multiple locations. We offer continuous learning, success defined by you, transformative leadership opportunities, and a diverse and inclusive culture.