Senior Data Engineer with Healthcare Background-Minneapolis, MN-Hybrid -Need Loc

Job title: Senior Data Engineer with Healthcare Background Location: Minneapolis, MN-Hybrid -Need Locals Only Longterm Need 10 Years EXP Must Job Summary We are seeking a highly skilled

Senior Data Engineer

with strong experience in

Azure Data Factory (ADF), Azure Databricks, Synapse Analytics, and Data Lake (ADLS)

to support enterprise-scale data initiatives in the

Healthcare domain . The ideal candidate will design, build, and optimize cloud-based data pipelines and architectures to enable advanced analytics, reporting, and data-driven healthcare decision-making.

Key Responsibilities

Design, develop, and implement

data pipelines and ETL processes

using

Azure Data Factory (ADF), Azure Databricks (PySpark), and Synapse Analytics

to ingest, process, and store healthcare data from diverse structured and unstructured sources.

Build and maintain

medallion data architectures (bronze-silver-gold layers)

to ensure scalability, reusability, and performance across analytics workloads.

Implement

real-time and batch data processing

solutions leveraging

ADF triggers, Event Hub, Service Bus Queues, and Stream Analytics

for timely data delivery and event-driven architectures.

Collaborate with

data analysts, data scientists, and business teams

to understand data requirements and translate them into efficient and automated data workflows.

Integrate data from multiple healthcare systems (EHR, EMR, claims, HL7/FHIR feeds, payer/provider systems, etc.) into centralized

Azure Data Lake

environments while ensuring compliance with

HIPAA and PHI data security standards .

Develop and manage

Linked Services, Datasets, and Data Flows

within ADF, optimizing for performance and cost efficiency.

Utilize

PolyBase and Synapse Analytics

for large-scale data loading and querying to support downstream BI and Power BI reporting.

Deploy CI/CD pipelines using

Azure DevOps

or

Jenkins , ensuring automated, version-controlled, and consistent deployment of data integration artifacts.

Create and maintain

technical documentation, data dictionaries, and data lineage

to support data governance and traceability.

Monitor, troubleshoot, and optimize

ADF pipelines and Databricks clusters , ensuring system reliability and timely data delivery.

Support

data migration initiatives

from on-premises (e.g., Oracle, Teradata, SQL Server) to

Azure Data Lake

and cloud-native platforms.

Implement data quality, validation, and audit mechanisms to ensure the accuracy and reliability of healthcare datasets.

Participate in sprint planning, code reviews, and cross-functional collaboration to deliver high-quality, production-ready data solutions.

Required Skills & Experience

10 years

of experience as a

Data Engineer , including at least

3 years

in a

Healthcare environment .

Strong proficiency in

Azure Data Factory (ADF v2) ,

Azure Databricks (PySpark) ,

Azure Synapse Analytics , and

ADLS Gen2 .

Hands‑on experience with

Azure Event hub ,

Service Bus ,

Logic Apps , and

Stream Analytics

for real‑time and event‑driven data integration.

Advanced

SQL

skills (T‑SQL, PL/SQL) and experience creating stored procedures, triggers, and complex queries for data transformation.

Experience working with

healthcare datasets

(EHR/EMR, HL7, FHIR, Claims, Clinical, or Patient Data) and understanding of

HIPAA compliance .

Proven ability to migrate data from

on‑prem systems (Oracle, Teradata, SQL Server)

to Azure cloud environments.

Experience implementing

DevOps CI/CD

for data projects using

Azure DevOps, Git, or Jenkins .

Familiarity with

data modeling, data warehousing concepts, and dimensional modeling .

Proficiency in

Python, PySpark , and scripting for data automation and transformation.

Strong analytical, problem‑solving, and communication skills with the ability to work cross‑functionally with business and technical teams.

Bachelor s degree in

Computer Science, Data Engineering, Information Systems, or related field .

Preferred Qualifications

Experience in

Microsoft Fabric

and

Power BI integration .

Exposure to

machine learning workflows

within Databricks or Azure ML.

Knowledge of

data governance frameworks

and

metadata management

tools.

Familiarity with

FHIR APIs ,

HL7 data integration , or

payers/providers data ecosystems .

Microsoft Azure certifications (e.g.,

DP‑203: Data Engineering on Microsoft Azure ) are a plus.

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