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Architect - Data Modeller

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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
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What you’ll work on

Full posting

The Data Modeler is responsible for the structural design of the platform's canonical and derived data assets.

  • Design schema-level tables for the Common Data Model (dimension, fact, bridge, reference)

  • Write field-level source-to-target mappings for every source-system feed

  • Specify how FHIR resources derive from CDM columns

  • Design data product schemas such as the patient mart and HEDIS aggregations

  • Review dbt model code against the spec

From the employer’s posting
The Data Modeler is responsible for the structural design of the platform's canonical and derived data assets. You will own the Common Data Model (CDM) at the schema level — the dimension, fact, bridge, and reference tables that hold normalized clinical, claims, and demographic data — and the source-to-target mappings (STTMs) that define how source-system data lands in CDM and how CDM data is reshaped into FHIR resources.
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
specify how every FHIR element derives from CDM columns, including cardinality, profile constraints, and terminology bindings
Design data product schemas — the longitudinal patient mart, population analytics aggregations, risk adjustment marts, HEDIS measure pre-aggregations
Review dbt model code for adherence to the spec, including column naming, hash key construction, SCD2 macro usage, and test coverage
Education & alternatives
Required Skills and Qualifications - 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
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Open 5 monthsWe first saw this posting 176 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

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May 11, 2026176 days ago
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225
Last seen by us
Nov 4, 2026

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Day 176

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From 589 similar postings that came down. Coming down is not always a hire.

Quantiphi is hiring

30 open jobs

Open jobs by the week we first saw them, last 12 weeks.

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  • 3% of open jobs were reposted
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See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • dbt
  • GCP
Where the posting names them
- Demonstrated ability to design conceptual, logical, and physical data models — dimensional modeling (Kimball), data vault, or hybrid patterns. This project uses a Kimball-influenced canonical model with SCD2 dimensions and per-source row preservation - 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
- Author and maintain unit specs at the model level under the spec-driven development framework. Each table has a versioned spec; model changes go through the spec review process before implementation - Collaborate with data engineers to translate model specs into dbt implementations. Review dbt model code for adherence to the spec, including column naming, hash key construction, SCD2 macro usage, and test coverage - 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. Profile findings drive STTM design
- Experience with Atlan or comparable governance and lineage tooling - Hands-on dbt authorship including macros, tests, and project structure - Familiarity with FHIR Implementation Guides beyond US Core (CARIN BB, Da Vinci, IPA)
- 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

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About the role

We file this job under Data Governance, by the work the posting describes.

Data governance staff keep a company's data accurate, documented and used within the rules. They agree what key fields mean, set up quality checks, track who owns each dataset and look after master data.

Postings ask for SQL, a governance tool such as Collibra or Informatica, knowledge of privacy and data rules, and a lot of work with other teams.

A data engineer builds the systems that move data; governance staff set and check the standards that data has to meet.

Job description

View original posting ↗

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.


If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Architect Data Modeler

Exp Range : 8 - 13 Years

Job Location : Mumbai , Bangalore, Trivandrum

Role Overview

The Data Modeler is responsible for the structural design of the platform's canonical and derived data assets. You will own the Common Data Model (CDM) at the schema level — the dimension, fact, bridge, and reference tables that hold normalized clinical, claims, and demographic data — and the source-to-target mappings (STTMs) that define how source-system data lands in CDM and how CDM data is reshaped into FHIR resources.

This role is hands-on. You will produce schema designs in collaboration with the architect, write STTM specifications that engineers implement against, and work with clinical informatics and source-system experts to ensure the model accurately reflects the data's clinical and operational meaning. Your output is the contract between source data and CDM, and between CDM and downstream consumers.

Key Responsibilities

  • 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 — EPIC HL7v2 ADT/ORU/ORM, Cerner HL7v2, ambulatory EHR feeds, state HIE CCDA, payer claims CSVs, FHIR ingestion. STTMs specify field-by-field source-path → CDM-column mapping with explicit transformation, NULL handling, and validation rules

  • Develop and maintain STTMs for FHIR serialization — for each in-scope US Core 6.1 resource (Patient, Encounter, Condition, Observation, Procedure, Practitioner, Organization, AllergyIntolerance), specify how every FHIR element derives from CDM columns, including cardinality, profile constraints, and terminology bindings

  • Design data product schemas — the longitudinal patient mart, population analytics aggregations, risk adjustment marts, HEDIS measure pre-aggregations. Each data product has a defined grain, columns, and refresh semantics

  • Author and maintain unit specs at the model level under the spec-driven development framework. Each table has a versioned spec; model changes go through the spec review process before implementation

  • Collaborate with data engineers to translate model specs into dbt implementations. Review dbt model code for adherence to the spec, including column naming, hash key construction, SCD2 macro usage, and test coverage

  • 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. Profile findings drive STTM design

  • Define and enforce reference data (REF) management practices — terminology crosswalks (LOINC, SNOMED, ICD-10, RxNorm, CPT), source-code-to-standard-code mappings, and the SCD2 patterns that govern reference data evolution

  • Document data dictionaries, lineage, and the canonical model glossary. Engage with Atlan or equivalent governance tooling to publish model documentation for downstream consumers

  • Work with clinical informaticists and source-system experts to validate that the model and STTMs accurately represent clinical reality. STTMs are the contract between engineering and clinical informatics; you own that contract

Required Skills and Qualifications

  • 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. This project uses a Kimball-influenced canonical model with SCD2 dimensions and per-source row preservation

  • 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

Nice-to-Have Skills

  • Direct experience with the Optum Health Data Engine canonical model or comparable healthcare canonical models (OMOP, PCORnet CDM, Sentinel)

  • Experience with master data management modeling — patient matching attributes, source-system identifier preservation, ECI lifecycle

  • Experience with Atlan or comparable governance and lineage tooling

  • Hands-on dbt authorship including macros, tests, and project structure

  • Familiarity with FHIR Implementation Guides beyond US Core (CARIN BB, Da Vinci, IPA)

  • Experience with data modeling tools (ER/Studio, Erwin, dbdiagram, SqlDBM) for diagram production

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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IN MH Mumbai Eureka

- 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. This project uses a Kimball-influenced canonical model with SCD2 dimensions and per-source row preservation - Strong SQL proficiency. Experience reading and reviewing dbt SQL models is required; ability to author dbt models is a plus
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