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:
712 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
712 years in
Data Engineering
Hands-on
Azure Cloud
and
Databricks
experience

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