Data Engineer

Company Description

Zigma LLC is a women-owned technology consulting and IT services start-up specializing in Big Data engineering, cloud data modernization, cloud architecture, and advanced analytics. Our mission is to empower organizations through secure, scalable, and high-performance digital ecosystems while maintaining a strong commitment to cybersecurity and compliance. We work with clients across various industries, including healthcare, telecom, and financial services, ranging from local businesses to enterprise-level corporations. Dedicated to fostering inclusion and women's leadership, we strive to deliver innovative solutions that drive operational efficiency and digital transformation. Zigma LLC combines technical expertise with a passion for empowering the next generation of women entrepreneurs.

Data Engineer (Mid-Level) – Hybrid | C2C | Healthcare

Locations:

East Bay Area, CA | Greater Los Angeles Area, CA | Oregon's Willamette Valley, OR | Greater Atlanta Area, GA

Employment Type:

C2C

Work Authorization:

US Citizens, Green Card, H4/L2/Any EAD, OPT/CPT Candidates.

Work Arrangement:

Hybrid

Openings:

3 per location

Experience:

7–12 years
Contract:

Long-term (12+ months, performance-based)

Preferred Education/Certification:

B.S/M.S. in Engineering Discipline with Computer Science, Data Engineering or relevant skills and certifications

Join a leading healthcare analytics team as a
Data Engineer
Work on
Azure Cloud
,
Databricks
, and modern
Data Pipelines
to drive insights from complex healthcare datasets. This is a
hybrid role
with opportunities to collaborate across multiple locations.

Key Responsibilities:

•   Design, build, and maintain
ETL/ELT Ingestion pipelines
on Azure Cloud

•   Collaborate with data scientists and analysts to ensure
data quality, governance, and availability

•   Implement
batch and streaming data processing
workflows

•   Optimize
data workflows and pipelines
for performance and scalability

•   Work with
HIPAA-compliant healthcare data

Technical Skills & Tools:

Programming & Scripting:
Python, SQL, Scala/Java
Data Processing Frameworks:
Apache Spark, Kafka, Airflow/Prefect
Databases:
Relational (PostgreSQL, MySQL, SQL Server), NoSQL (MongoDB, Cassandra), Data Warehouses (Snowflake, Redshift)
Data Formats:
CSV, JSON, Parquet, Avro, ORC
Version Control & DevOps:
Git, Azure DevOps, CI/CD pipelines
Cloud & Containerization:
Azure Cloud, Docker, Kubernetes, Terraform

Core Skills:

•   ETL/ELT Ingestion pipeline design

•   Batch & streaming data processing

•   Data modelling (star/snowflake schema)

•   Performance optimization & scalability

•   Data governance and security

Must-Have:

•   7–12 years in
Data Engineering

•   Hands-on
Azure Cloud
and
Databricks
experience

•   M.S. in Data Science or relevant certifications (Databricks/Data Science)