Data Engineer (San Francisco) at Zigma LLC

Company DescriptionZigma 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 | HealthcareLocations: East Bay Area, CA | Greater Los Angeles Area, CA | Oregon's Willamette Valley, OR | Greater Atlanta Area, GAEmployment Type: C2CWork Authorization: US Citizens, Green Card, H4/L2/Any EAD, OPT/CPT Candidates.Work Arrangement: HybridOpenings: 3 per locationExperience: 712 yearsContract: 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 certificationsJoin 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 CloudCollaborate with data scientists and analysts to ensure data quality, governance, and availabilityImplement batch and streaming data processing workflowsOptimize data workflows and pipelines for performance and scalabilityWork with HIPAA-compliant healthcare dataTechnical Skills & Tools:Programming & Scripting: Python, SQL, Scala/JavaData Processing Frameworks: Apache Spark, Kafka, Airflow/PrefectDatabases: Relational (PostgreSQL, MySQL, SQL Server), NoSQL (MongoDB, Cassandra), Data Warehouses (Snowflake, Redshift)Data Formats: CSV, JSON, Parquet, Avro, ORCVersion Control & DevOps: Git, Azure DevOps, CI/CD pipelinesCloud & Containerization: Azure Cloud, Docker, Kubernetes, TerraformCore Skills:ETL/ELT Ingestion pipeline designBatch & streaming data processingData modelling (star/snowflake schema)Performance optimization & scalabilityData governance and securityMust-Have:712 years in Data EngineeringHands-on Azure Cloud and Databricks experienceM.S. in Data Science or relevant certifications (Databricks/Data Science)