Data Modeler

Akaasa Technologies; Massachusetts; Remote; USD 120,000 - 180,000; Full time

Job summary

Akaasa Technologies in the United States (Remote) is seeking a Data Modeler to support a Databricks unified data platform for commercial life sciences.

You will design data models across patient and HCP domains, establish medallion architecture, and collaborate with business SMEs and data engineers. This role emphasizes governance, privacy, and scalable data products like Patient Journey and HCP 360.

Qualifications

• Proficient in enterprise and dimensional data modeling for data platforms.
• 3+ years with commercial life sciences data domains and data governance.
• 5+ years SQL experience; 3+ years with Databricks Delta Lake.

Responsibilities

• Design conceptual, logical, and physical data models across core domains (Patient, HCP, HCO, product, payer).
• Define modeling standards across Bronze, Silver, Gold medallion layers in Databricks Delta Lake.
• Create source-to-target mappings and reusable data structures for enterprise consumption.
• Collaborate on identity resolution, data governance, lineage, and patient privacy.

Skills

SQL

Databricks Delta Lake

Commercial Life Sciences Data

Job description

Title: Data Modeler Commercial Life Sciences

Location: Remote

POSITION OVERVIEW

We are seeking a Data Modeler to join our team in supporting a Databricks unified data platform initiative. The primary focus is building a common data model and developing reusable, high-impact data products such as Patient Journey and HCP 360. This role bridges business strategy and technical execution across critical commercial life sciences data domains.

DAY-TO-DAY RESPONSIBILITIES

• Design conceptual, logical, and physical data models across patient, HCP, HCO, product, payer, and commercial activity domains.
• Define and maintain modeling standards across bronze, silver and gold medallion layers on Databricks Delta Lake.
• Establish harmonized entities in the silver layer and consumption-ready data products in the Gold layer.
• Translate complex business requirements into entity relationships, data grain, shared dimensions, business definitions, and historical tracking strategies.
• Develop detailed source-to-target mappings and build reusable data structures that support multiple downstream data products.
• Collaborate closely with business SMEs, architects, and data engineers on identity resolution, data quality, lineage, governance, and patient privacy compliance.

REQUIRED SKILLS

• SQL (5+ years) Expert ability with enterprise, dimensional, and canonical data modeling techniques.
• Databricks & Delta Lake (3+ years) Hands-on experience designing schemas for Medallion Architecture (Bronze, Silver, Gold).
• Commercial Life Sciences Data (3+ years) Deep knowledge of IQVIA, Symphony Health, Veeva CRM, HCP/HCO reference data, Specialty Pharmacy/Patient Hub feeds, and Payer/Formulary datasets.

ADDITIONAL DESIRED SKILLS

• Experience designing scalable data models for Patient Journey Analytics and HCP 360 use cases.
• Familiarity with data granularity, refresh cycles, coverage limitations, and provider linkage methodologies.
• Background in data governance, data lineage, and HIPAA/patient privacy requirements.

CANDIDATE PROFILE

The ideal candidate is a technical yet business-savvy Data Modeler with deep domain expertise in Commercial Life Sciences. They thrive in cross-functional environments, comfortably communicating technical schema designs to business SMEs while supplying clear specifications to data engineers.

Job Responsibilities

• Design robust conceptual, logical, and physical data models across core domains including Patient, HCP, HCO, Product, and Payer.
• Establish schema and modeling standards for bronze, silver, and gold layers using Databricks Delta Lake and Medallion Architecture.
• Create source-to-target mappings, define business rules, and design reusable data structures to support enterprise consumption.
• Collaborate with engineering, architecture, and business teams on identity resolution, data governance, and patient privacy frameworks.