Data Modeller

PwC; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC in Hyderabad seeks an experienced data modeller to architect scalable models across conceptual, logical and physical layers for healthcare and pharma domains. You will define platform-agnostic models with explicit grains and materialization, ensuring lineage and governance.

You will collaborate with data engineers, clinical and BI stakeholders to produce STTM documents and metadata dictionaries, while upholding privacy-by-design and HIPAA/PII considerations where applicable.

Qualifications

• Bachelor's degree is required.
• At least 4 years of experience in data modelling.
• Proficiency in English, both written and oral.

Responsibilities

• Create conceptual, logical and physical data models as standalone artifacts.
• Develop enterprise ER diagrams and data dictionaries read by stakeholders.
• Design semantic and metrics layers for BI tools to enable self-serve analytics.
• Translate reporting needs into durable, reusable model structures.
• Reverse engineer and optimize schemas and data pipelines for performance.

Skills

Data modeling

Data Vault 2.0

SQL

Dimensional modelling

ETL/ELT pipelines

Education

Bachelor's degree

Tools

Erwin Data Modeler

ER/Studio

SqlDBM

PowerDesigner

Snowflake

Databricks

dbt

Airflow

Job description

Responsibilities

• Produce each modelling layer as a reviewable, standalone artifact - a conceptual model with clean definitions, a platform-agnostic logical model with explicit grain, and a physical model committed to concrete types, clustering, and materialization.
• Build and maintain complex data diagrams and enterprise entity-relationship maps that stakeholders can actually read and trust.
• Spec and design end-to-end data products from the dashboard / self-serve semantic layer at the top, down through business-object mapping, into data models and the physical store.
• Design semantic / metrics layers that plug cleanly into BI tools (Power BI, Tableau) so analysts and business users can self-serve without re-deriving logic.
• Translate reporting and KPI requirements into durable model structures rather than one-off pulls.
• Forward / Reverse engineering: generate physical SQL- DDL from logical models, and reverse-engineer existing (often legacy) healthcare and commercial databases into clean visual schemas.
• Query optimization: Advanced ANSI SQL and analytical queries to parse hierarchical and longitudinal healthcare data (patient journeys, claims histories, HCP/HCO hierarchies).
• Performance tuning: Indexing strategies, partitioning, clustering keys, distribution styles, and execution-plan analysis to keep queries fast on very large patient / claims / sales datasets.
• Lakehouse paradigm: Model for decoupled storage and compute with practical Delta Lake / lakehouse experience (medallion architecture, incremental models).
• Author and maintain Source-to-Target Mapping (STTM) documents, data definitions, and metadata dictionaries.
• Define and enforce data lineage, data-quality KPIs, and reconciliation logic so the model is auditable end-to-end.
• Create data structures for US pharma domains — Electronic Health Records (EHR/EMR), clinical performance metrics, and/or pharma commercial data (sales, patient, market access, claims, patients).
• Model the messy realities of the domain: HCP/HCO master data, longitudinal patient/claims data, specialty pharmacy feeds, and affiliation hierarchies.
• Bake privacy-by-design into the models to support HIPAA compliance and general data-security guidelines (PHI/PII handling, masking, role-based access, de-identification).
• Work shoulder-to-shoulder with data engineers, clinical/commercial stakeholders, and BI analysts to optimize pipelines and make sure reporting requirements are genuinely met — not just technically satisfied.

What You Must Have

• At least a Bachelor's degree
• At least 4 years of experience
• Oral and written proficiency in English required

What Sets You Apart

• Proven experience across conceptual logical physical modelling for warehouses, marts, and lakehouses (star / snowflake schemas, dimensional modelling; Data Vault 2.0 a strong plus).

Additional Technical Skills

• Hands-on with a modelling tool: erwin Data Modeler, ER/Studio, SqlDBM, or PowerDesigner — including forward-engineering DDL and reverse-engineering existing schemas.
• Expert ANSI SQL with real performance-tuning depth (execution plans, partitioning, clustering).
• Production experience on at least one modern cloud data platform: Snowflake and/or Databricks / Delta Lake (Redshift, BigQuery, Synapse also relevant).
• Comfort with the transformation layer — dbt for physical modelling / ELT and exposure to orchestration (Airflow, ADF).
• Demonstrated ownership of STTMs, data dictionaries, metadata, lineage and profiling as first-class deliverables.
• Experience with healthcare and/or pharma / life-sciences data. Strong signal: familiarity with IQVIA / IMS, Symphony/claims data, Veeva, EHR/EMR, RWD/RWE, Digital Marketing Channels and MDM for HCP/HCO.
• Working understanding of HIPAA and PHI/PII handling.