Live opening · Posted 5 days ago

Data Modeler

PwC Acceleration Center India · Bengaluru East, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyPwC Acceleration Center India
LocationBengaluru East, Karnataka, India (On-site)
Work modeNo
SkillsAWS, Azure, GCP
SourceLinkedin
ListedPosted 5 days ago

About the role

Description supplied by the original job listing.

The Opportunity
Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.
As a Data Modeler you will shape data structures that support data and analytics engineering within our Cloud Engineering, Data & Analytics practice, helping translate business needs into practical data models and design choices. As a Manager you will lead teams, coach junior professionals, and manage workstreams while bringing together planning, delivery oversight, and thoughtful problem solving to help drive client outcomes. In this role at PwC, you will contribute to data modernisation efforts by developing conceptual, logical, and physical models, supporting data governance activities, and collaborating across teams to improve how data is organized, accessed, and used.
Responsibilities
Leading data modeling workstreams across data engineering initiatives, translating business needs into scalable logical and physical models
Designing dimensional, warehouse, and lakehouse structures that support analytics, reporting, and downstream data consumption
Reviewing source system structures, business rules, and transformation logic to define accurate data relationships and mappings
Applying Snowflake, Databricks, Azure Data Factory, and data pipeline tools to shape, transform, and validate data assets
Collaborating with architects, engineers, and client stakeholders to align model design with data strategy and platform architecture
Identifying data quality, performance, and integration issues and driving remediation actions through iterative design reviews
Mentoring junior team members on modeling standards, documentation practices, and technical delivery methods
Managing deliverable timelines, prioritizing work across multiple requests, and adapting design decisions as requirements evolve
What You Must Have
At least a Bachelor's degree
At least 8 years of experience
Oral and written proficiency in English required
Well versed in Data Modeling tools like ER/Studio, Erwin Data Modeler, Data Vault, Toad Data Modeler etc.
Hands on experience of working in the Cloud technologies – AWS/Azure/GCP
End to end data and analytics solutions design experience using cloud technologies- AWS S3, Spark, EMR, Data bricks, MPP databases, Snowflake right from Ingestion to Transformation to Consumption using various methods including API delivery or similar knowledge in alternate cloud services
Strong skills in SQL, SQL Procedure builds
Strong skills in analyzing Data Warehouse performance issues and resolutions using various methods/ techniques
Strong analytical skills and troubleshooting skills
What Sets You Apart
Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
Demonstrating data modeling experience across enterprise data platforms
Utilizing dimensional modeling and data warehouse design techniques
Managing data integration, transformation, and validation workstreams
Leading teams through complex data architecture decisions
Applying Snowflake, Databricks, AWS, or Azure Data Factory

Work arrangement
No

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