Architect – Data Modeller

Quantiphi; Mumbai; On-site; INR 2,800,000 - 4,000,000; Full time

Job summary

Jobtailor in Mumbai seeks a Data Modeler to design canonical and derived data assets for healthcare analytics, collaborating with architects and data engineers.

You will model the DIM/FACT/BRIDGE/REF structures, develop STTMs, and implement SCD2 patterns while aligning with FHIR, HL7, and US Core standards on a cloud data platform.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
• 5+ years of data modeling experience for large-scale data warehouses, data lakes, or data platforms.
• Ability to design conceptual, logical, and physical data models (Kimball, data vault, or hybrid).
• Strong SQL proficiency and experience reading dbt SQL models.
• Experience modeling for analytical and operational data layers for FHIR API consumers.
• Hands-on with healthcare data standards (HL7v2, CCDA, FHIR R4) and crosswalks.
• Familiarity with US Core profiles and FHIR Bundle composition.
• Experience producing STTMs at field-level for multi-source integration.
• Knowledge of SCD2 patterns and late-arriving data implications.
• Familiarity with terminology systems (LOINC, SNOMED CT, ICD-10, CPT, RxNorm).
• Experience with Google Cloud Platform data services and Iceberg.

Responsibilities

• Own the schema-level design of the Common Data Model: DIM, FACT, BRIDGE, REF.
• Design columns, NULL semantics, hash keys, SCD2, and partitioning with architects.
• Develop and maintain Source-to-Target Mappings (STTMs) for all source feeds.
• Design data product schemas for longitudinal patient marts and analytics aggregations.
• Author and maintain unit specs under a spec-driven framework.
• Collaborate with data engineers to translate specs into dbt implementations.
• Profile source systems to identify quality issues and modeling implications.
• Define and enforce reference data management across terminology crosswalks.

Skills

Data modeling

SQL

dbt

Dimensional modeling

Data vault

SCD2

STTM

FHIR/HL7

US Core

GCP & cloud data platforms

Iceberg

Data profiling

Reference data management

Documentation

Education

Bachelor's or Master's in Computer Science/Information Systems

Quantitative field preference

Tools

dbt SQL models

Google Cloud Platform (GCP)

BigLake/Dataproc

Iceberg table format

Cloud Storage

Job description

Responsibilities

• The Data Modeler is responsible for the structural design of the platform's canonical and derived data assets.
• Own the schema-level design of the Common Data Model — DIM (patient, person, encounter, provider, organization), FACT (observation, diagnosis, procedure, medication administration, claim line, encounter), BRIDGE (relationship-qualifier-aware), and REF (terminology and crosswalk) tables.
• Design columns, types, NULL semantics, hash key composition, SCD2 patterns, and partitioning strategies in coordination with the architect.
• Develop and maintain Source-to-Target Mappings (STTMs) for every source-system feed.
• Design data product schemas — the longitudinal patient mart, population analytics aggregations, risk adjustment marts, HEDIS measure pre-aggregations.
• Author and maintain unit specs at the model level under the spec-driven development framework.
• Collaborate with data engineers to translate model specs into dbt implementations.
• Participate in source-system data profiling — analyze sample data from each source to identify quality issues, edge cases, and modeling implications before specs are finalized.
• Define and enforce reference data (REF) management practices — terminology crosswalks (LOINC, SNOMED, ICD-10, RxNorm, CPT).

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, or a related quantitative field.
• 5+ years of data modeling experience for large-scale data warehouses, data lakes, or data platforms.
• Demonstrated ability to design conceptual, logical, and physical data models — dimensional modeling (Kimball), data vault, or hybrid patterns.
• Strong SQL proficiency.
• Experience reading and reviewing dbt SQL models is required; ability to author dbt models is a plus.
• Experience modeling for analytical and operational data layers simultaneously — understanding how a normalized canonical model serves both downstream analytics and FHIR API consumers.
• Hands-on experience with healthcare data standards — HL7v2 segment-level structure, CCDA document structure, and FHIR R4 resource models.
• Familiarity with US Core profiles and FHIR Bundle composition.
• Experience producing source-to-target mappings (STTMs) at field-level granularity for multi-source data integration projects
• Experience modeling SCD2 patterns and the operational implications of late-arriving data, restatement, and version closure.
• Experience with terminology systems used in healthcare — LOINC, SNOMED CT, ICD-10, CPT, RxNorm — and their crosswalk patterns.
• Familiarity with Google Cloud Platform data services (Cloud Storage, BigLake, Dataproc) and open table formats. Direct Iceberg experience is a plus.
• Strong written communication skills. STTMs and model documentation are read across engineering, QA, clinical, and governance audiences.