IT|Data Architecture - Associate Data Architect I

Mandatory areas – Senior Data Engineer (Healthcare Clinical Data): 8+ years

Must Have skills

Senior Data Engineer (Healthcare Clinical Data) with expertise in:

• Databricks
• Snowflake
• PySpark/Spark
• Healthcare Clinical Data
• Healthcare Data Standards (HL7, FHIR, ICD-10, CPT, etc.)

This is a domain-heavy role, where healthcare knowledge is just as important as technical skills.

Mandatory, if Applicable

Domain Experience (If any) – Healthcare Clinical Data

Must have Certifications – NA

Prior UST experience – NA

If yes, provide dates, details of account/project

Location

Onsite Requirement – Both Onsite and Remote is ok but onsite is always preferred

Number of days onsite – 5 days

If onsite, provide Office Address – US- Long Beach, CA

Summary Information

Request Type

Standard

Geography

United States

Labor Category

Contingent Worker

Procurement Type

Contingent Labor

Tax Work Location

USA-Working from Home

Client Job Description

JD 1

Data Engineer, Healthcare Clinical Data, Databricks & Snowflake (Onshore) Role Summary

• We are looking for an experienced Data Engineer with strong healthcare clinical data knowledge and hands-on expertise in Databricks and Snowflake.

This person will work closely with client stakeholders, the Data Architect, data science teams and offshore engineers to build and maintain scalable clinical data pipelines and datasets that support predictive analytics.

The role will also coordinate day-to-day engineering activities with the offshore team and help ensure smooth delivery.

Key Responsibilities

• Work directly with client stakeholders to understand clinical data requirements, clarify source-to-target mappings and translate requirements into scalable data engineering solutions.
• Develop and maintain data pipelines using Databricks, Snowflake, Spark/PySpark and SQL.
• Build and manage data layers within a Lakehouse/Medallion architecture, including Bronze, Silver and Gold datasets using Delta Lake and related data platforms.
• Design and implement data ingestion, transformation and integration between Databricks, Snowflake and upstream/downstream healthcare systems.
• Ingest, transform and standardize clinical data from EHR/EMR and other healthcare sources, including encounters, diagnoses, procedures, labs and medications.
• Work with healthcare data standards such as HL7, FHIR, CCD, ICD-10, CPT, LOINC, SNOMED and RxNorm to prepare standardized and analytics-ready datasets.
• Build high-quality data foundations for predictive analytics use cases such as readmission risk, risk stratification and care gaps.
• Partner with Data Architects and data science teams to prepare curated datasets and features required for machine learning and predictive models.
• Implement data quality checks, reconciliation, exception handling, monitoring and logging to ensure reliable data pipelines.
• Apply data governance, lineage, access controls and HIPAA/PHI security requirements across Databricks, Snowflake and the broader data ecosystem.
• Optimize Spark, SQL, Databricks and Snowflake workloads for performance, scalability and cost.
• Coordinate with offshore engineers on requirements, development, testing and issue resolution, while providing regular delivery updates to client and project stakeholders.
• Troubleshoot pipeline and data issues, identify root causes and support timely resolution across development and production environments.

Required Skills & Experience

• 6+ years of experience in data engineering, with strong exposure to healthcare and clinical data.
• Good understanding of healthcare clinical data and standards including HL7, FHIR, CCD, ICD-10, CPT, LOINC, SNOMED and RxNorm.
• Strong hands-on experience with Databricks, Spark/PySpark, SQL, Delta Lake, Unity Catalog and Databricks Workflows.
• Strong working experience with Snowflake, including data loading, transformation, data modeling, performance optimization and security/access controls.
• Experience building ETL/ELT pipelines and implementing Lakehouse and Medallion architectures.
• Experience integrating and moving data across Databricks, Snowflake and cloud-based data platforms.
• Experience preparing data for predictive analytics, advanced analytics or machine learning use cases.
• Good working knowledge of Azure or AWS cloud environments.
• Understanding of healthcare data security, HIPAA and PHI handling requirements.
• Strong SQL skills with experience in data transformation, performance optimization and data quality frameworks.
• Good communication and stakeholder management skills, with experience working in an onshore-offshore delivery model.

Status

Open

Has Assignments

No

Request Information

Request

IT|Data Architecture - Associate Data Architect I

Qty

1

Candidate Submission Limit Per Supplier

3

Candidate Submission Limit Per Request

0

Desired Start Date

11/23/2026

End Date

12/31/2026

Hrs/Wk

40.00

MSP Owner

Mishra, Raghuvendra

Client Job Description

JD 1

Data Engineer, Healthcare Clinical Data, Databricks & Snowflake (Onshore) Role Summary

• We are looking for an experienced Data Engineer with strong healthcare clinical data knowledge and hands-on expertise in Databricks and Snowflake.

This person will work closely with client stakeholders, the Data Architect, data science teams and offshore engineers to build and maintain scalable clinical data pipelines and datasets that support predictive analytics.

The role will also coordinate day-to-day engineering activities with the offshore team and help ensure smooth delivery. Key Responsibilities

• Work directly with client stakeholders to understand clinical data requirements, clarify source-to-target mappings and translate requirements into scalable data engineering solutions.
• Develop and maintain data pipelines using Databricks, Snowflake, Spark/PySpark and SQL.
• Build and manage data layers within a Lakehouse/Medallion architecture, including Bronze, Silver and Gold datasets using Delta Lake and related data platforms.
• Design and implement data ingestion, transformation and integration between Databricks, Snowflake and upstream/downstream healthcare systems.
• Ingest, transform and standardize clinical data from EHR/EMR and other healthcare sources, including encounters, diagnoses, procedures, labs and medications.
• Work with healthcare data standards such as HL7, FHIR, CCD, ICD-10, CPT, LOINC, SNOMED and RxNorm to prepare standardized and analytics-ready datasets.
• Build high-quality data foundations for predictive analytics use cases such as readmission risk, risk stratification and care gaps.
• Partner with Data Architects and data science teams to prepare curated datasets and features required for machine learning and predictive models.
• Implement data quality checks, reconciliation, exception handling, monitoring and logging to ensure reliable data pipelines.
• Apply data governance, lineage, access controls and HIPAA/PHI security requirements across Databricks, Snowflake and the broader data ecosystem.
• Optimize Spark, SQL, Databricks and Snowflake workloads for performance, scalability and cost.
• Coordinate with offshore engineers on requirements, development, testing and issue resolution, while providing regular delivery updates to client and project stakeholders.
• Troubleshoot pipeline and data issues, identify root causes and support timely resolution across development and production environments.

Required Skills & Experience

• 6+ years of experience in data engineering, with strong exposure to healthcare and clinical data.
• Good understanding of healthcare clinical data and standards including HL7, FHIR, CCD, ICD-10, CPT, LOINC, SNOMED and RxNorm.
• Strong hands-on experience with Databricks, Spark/PySpark, SQL, Delta Lake, Unity Catalog and Databricks Workflows.
• Strong working experience with Snowflake, including data loading, transformation, data modeling, performance optimization and security/access controls.
• Experience building ETL/ELT pipelines and implementing Lakehouse and Medallion architectures.
• Experience integrating and moving data across Databricks, Snowflake and cloud-based data platforms.
• Experience preparing data for predictive analytics, advanced analytics or machine learning use cases

.

• Good working knowledge of Azure or AWS cloud environments.
• Understanding of healthcare data security, HIPAA and PHI handling requirements.
• Strong SQL skills with experience in data transformation, performance optimization and data quality frameworks.
• Good communication and stakeholder management skills, with experience working in an onshore-offshore delivery model.

General Information

Job Description

Proficiency

Leverage expertise in a technology area (e.g. Infromatica Transformation, Terradata data warehouse, Hadoop, Analytics), Responsible for Architecture for a small/mid-size projects.

Comments for Suppliers

CPT,Apache Spark,Access Control,Databricks,Delta Lake,LOINC,Machine Learning

Skills

Skills

Category

Name

Required

Importance

Experience

No items to display.

Additional Skills

Data Lakes,Data Governance,Snowflake,ICD-10-CM