Lead Databricks Data Architect (Healthcare Domain)
Lead Databricks Data Architect (Healthcare Domain)
Location: Multiple Locations Across India/US
Employment Type: Full-Time
Department: Enterprise Data & Analytics / Health Informatics
Experience Level: Senior / Lead (8+ years of data architecture, 3+ years focused on Databricks)
About the Role
We are seeking an experienced and visionary Databricks Data Architect with deep expertise in the Healthcare domain to design, build, and scale our next-generation Lakehouse platform. In this role, you will be the technical authority bridging clinical/healthcare data needs with modern cloud data engineering practices.
You will lead the transition and optimization of clinical, claims, operational, and EHR data into a unified, secure Databricks Lakehouse architecture—enabling real-time analytics, machine learning, and advanced clinical intelligence while ensuring strict adherence to healthcare compliance standards (HIPAA, HITRUST, HITEC).
Key Responsibilities
Architecture & Strategy:
- Design, architect, and deliver enterprise-scale Lakehouse solutions on the Databricks platform (Azure Databricks or AWS Databricks) tailored for complex healthcare datasets.
- Define data ingestion, transformation, storage, and consumption patterns across Bronze, Silver, and Gold medallion layers.Healthcare Domain Modeling:
- Design robust data models supporting standard healthcare ontologies and formats, including HL7, FHIR, DICOM, ICD-10, CPT, LOINC, SNOMED CT, as well as claims (837/835) and clinical EHR feeds (Epic, Cerner).
- Build scalable pipelines for population health, patient journey mapping, risk stratification, and quality reporting (e.g., HEDIS, CMS Star Ratings).Data Governance & Compliance:
- Implement unified governance, access control, and auditing using Databricks Unity Catalog.
- Enforce strict data security, encryption (at rest and in transit), PHI/PII masking, tokenization, and compliance with HIPAA, HITECH, and HITRUST requirements.Engineering Excellence & Performance:
- Optimize Delta Lake tables using partitioning, Z-Ordering, Liquid Clustering, and Auto-loader for high-volume streaming and batch ingestion.
- Oversee pipeline orchestration (Databricks Workflows, dbt, Apache Airflow) and CI/CD deployment pipelines using Terraform and Git.Collaboration & Leadership:
- Partner closely with clinical informaticists, biostatisticians, data scientists, and business stakeholders to translate clinical needs into high-performing data architectures.
- Mentor senior and mid-level data engineers on modern Lakehouse design patterns and Spark performance tuning.
Required Qualifications
- Healthcare Experience:
- Minimum 4+ years of direct experience working with healthcare data (payer claims, hospital/provider EHR data, clinical trials, or medical imaging).
- Hands-on knowledge of healthcare data standards (FHIR, HL7, OMOP Common Data Model, DICOM) and terminology/coding systems.
- Databricks & Cloud Expertise:
- 3+ years of dedicated, hands-on experience architecting and implementing Databricks solutions (Delta Lake, Unity Catalog, Spark SQL, PySpark).
- Strong expertise on a major cloud platform: Azure (Azure Data Factory, ADLS Gen2, Synapse) or AWS (S3, Glue, Athena).
- Data Engineering & Modeling:
- Proficiency in Python, PySpark, and advanced SQL.
- Deep experience with dimensional modeling, Data Vault, or standard healthcare schemas (e.g., OMOP).
- Security & Governance:
- Proven experience managing PHI/PII, implementing Role-Based Access Control (RBAC), and meeting HIPAA compliance requirements in a cloud ecosystem.
- Education:
- Bachelor’s or Master’s degree in Computer Science, Health Informatics, Data Engineering, or a related field (or equivalent practical experience).
Preferred / Nice-to-Have Qualifications
- Certifications:
- Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Associate / Professional.
- Cloud Architect Certification (AWS Certified Solutions Architect, Azure Solutions Architect Expert).
- Experience with dbt (data build tool) integrated with Databricks.
- Familiarity with real-time streaming architectures using Kafka or Event Hubs.
- Experience supporting downstream ML/AI workloads (e.g., Databricks Feature Store, MLflow, clinical NLP).