Data Engineer (San Jose)

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)