Data Engineer

Design and deploy scalable ETL / ELT pipelines

to ingest, transform,

and load clinical data from diverse sources (EMRs,  labs, IoT devices, data

lakes, FHIR / HL7 APIs), including Azure and Snowflake.

Architect and optimize Microsoft Azure and Snowflake

environments

for clinical data storage, extraction, transformation, and loading, machine

learning operations (MLOps) performance tuning, cost management, and secure

data sharing.

Ensure compliance with healthcare regulations

(HIPAA, GDPR) by

implementing data anonymization, encryption, and audit trails.

Collaborate with clinical stakeholders

to translate business

requirements into technical solutions for analytics and reporting.

Develop and maintain data governance frameworks

, including metadata

management, data lineage, and quality checks (e.g., validation of lab results,

patient demographics).

Automate data pipelines

using orchestration tools (e.g., Apache

Airflow, Prefect) and integrate real -time streaming solutions (e.g., Kafka)

where applicable.

Build and maintain documentation

for data models,

pipelines, and processes to ensure reproducibility and transparency.

Advanced

proficiency in

Snowflake

(Snowpipe, Time Travel, Zero -Copy Cloning) and

SQL for complex transformations.

Hands -on

experience with

ETL / ELT tools

(Apache Spark, AWS Glue, Azure Data

Factory) and cloud platforms (AWS, Azure, GCP).

Strong

programming skills in

Python / Scala

(Pandas, PySpark) for data scripting

and automation.

Familiarity

with healthcare data formats (OMOP, FHIR, HL7, DICOM) and clinical workflows.

Expertise in

federated learning and running large jobs on high -performance computing servers

is a plus.

Data Governance : Ability to implement

data quality frameworks (e.g., Great Expectations) and metadata management

tools.

Regulatory Compliance :

Proven experience

securing PHI / PII data and adhering to HIPAA / GDPR requirements.

Problem -Solving : Ability to

troubleshoot pipeline failures, optimize query performance, and resolve data

discrepancies.

Collaboration : Strong communication

skills to work with cross -functional teams (clinicians, analysts, IT).

Requirements

Snowflake

SnowPro Core Certification (or higher).

AWS / Azure / GCP

Data Engineering Certification (e.g., AWS Certified Data Analytics, Azure Data

Engineer Associate).

Running

jobs on high -performance computing servers

Healthcare -specific

certifications (e.g., HL7 FHIR Certification, Certified Health Data Analyst

(CHDA)).

Security

certifications (e.g., CISSP, CIPP) for handling sensitive clinical data.

3+ years of experience in data engineering, with 2+ years focused

on

healthcare / clinical data

(e.g., hospitals, EMR systems, clinical

trials).

2+ years of hands -on experience with

Snowflake

in

production environments.

Proven track record of building ETL pipelines for large -scale clinical

datasets.

Experience with OMOP CDM, Epic / Cerner EHR systems, or clinical

data lakes.

Exposure to DevOps practices (CI / CD, Terraform) and Agile

methodologies.

Some front -end development is preferred.