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Ernst & Young

Global professional services: consulting, assurance, tax

EYP-Dna-Manager

Data EngineeringPosted on Nov 10
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • Minimum of 9 years of total experience, including 6 or more years in data warehousing or business intelligence.
  • At least 6 years of hands-on professional experience creating and implementing data warehouses on client engagements and enhancing data warehouses.
  • Strong knowledge of data architecture for staging and reporting schemas, data models, and cutover strategies using industry-standard tools and technologies.
  • Experience designing and implementing medium-to-complex on-premises-to-cloud migrations using a major cloud platform such as AWS, Azure, or GCP.
  • At least 3 years of experience with Azure database offerings, including relational, NoSQL, and data warehouse services.
  • At least 2 years of hands-on experience with Azure Data Factory, Kafka, Azure Data Explorer, Storage, Azure Data Lake, Azure Synapse Analytics, Azure Analysis Services, and Databricks.
  • At least 3 years of hands-on database design, modeling, and integration experience with relational sources such as SQL Server, Oracle, MySQL, Azure SQL, and Azure Synapse.
  • Knowledge and direct experience with business intelligence reporting tools such as Power BI, Alteryx, OBIEE, Business Objects, Cognos, Tableau, MicroStrategy, and SSAS Cubes.
  • Hands-on or strong working knowledge of ontology design, graph databases, and knowledge graph modeling.
  • Working knowledge of RAG architectures, vector databases or embedding stores, and feature store concepts.
  • Experience building AI-assisted or agentic data pipelines, or strong familiarity with autonomous orchestration frameworks.
  • Experience with the software development life cycle and product development processes such as installation, upgrades, and namespace management.
  • A bachelor's degree or equivalent in Computer Science or a related field is required; an advanced degree or equivalent business experience is preferred.
  • Hands-on data engineering experience, including building analytical data records and manipulating and analyzing large volumes of data.
  • Experience preparing data for AI/ML consumption, including data-labeling strategies, training-data curation, and structured and unstructured data readiness.
  • Demonstrated ability to use hypothesis-driven problem solving and translate business requirements into data or technical specifications.
  • At least 10 to 12 years of relevant work experience in a Big Four or technology/consulting setting.
  • Willingness to mentor team members.
  • Willingness to travel extensively and work at client sites or practice office locations.

Responsibilities

  • Evaluate and select data warehousing and AI-enablement tools for business intelligence, data population, data management, metadata management, and warehouse administration across on-premises and cloud engagements.
  • Design, develop, and test workflows in ETL tool environments, including GUI- or canvas-based tools.
  • Design and build AI-ready data pipelines, including agentic orchestration, autonomous quality monitoring, and self-healing capabilities.
  • Implement ontology designs, knowledge graphs, and graph database solutions for Graph RAG and advanced analytics use cases.
  • Build and manage feature stores, embedding pipelines, and vector stores for AI/ML workloads.
  • Prepare design documentation, including data mappings, technical specifications, production support documentation, data dictionaries, and test cases.
  • Provide technical guidance to data warehouse, business intelligence, and AI-enablement developers.
  • Coordinate with technology users to design and implement data governance, data harvesting, cloud implementation strategy, AI data readiness, privacy, and security.
  • Conduct Data & AI maturity assessments for strategic engagements and translate findings into actionable roadmaps.
  • Follow ETL and data warehouse development best practices.
  • Own data orchestration, ingestion, ETL, and reporting architecture for on-premises and cloud environments, including Azure, AWS, and GCP.
  • Assist the team with performance tuning for ETL and database processes.

Desired Qualifications

  • Exposure to Graph RAG, LangChain/LlamaIndex, and agentic AI frameworks for data orchestration.
  • Experience with RFP and vendor evaluations for data and AI platforms.
  • Experience with industry benchmarking and current-state/future-state data landscape assessments.
  • Ability to think strategically and end-to-end with a results-oriented mindset.
  • Ability to build rapport within the firm and earn client trust.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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