Data Engineer with a client at Irvine, CA
Contract to hire.
Position Summary
The Engineer, Data Intelligence & Business Analytics designs, develops, and supports scalable data integration and analytics solutions using Snowflake, dbt, Matillion, Python, and cloud technologies.
This role partners with business and technical stakeholders to deliver trusted healthcare data, including Epic data, for reporting, analytics, and AI-driven initiatives. The engineer is responsible for building high-quality ETL/ELT pipelines, optimizing data performance, improving data quality, and supporting enterprise analytics and machine learning use cases.
Key Responsibilities
- Design and develop ETL/ELT pipelines using Snowflake, dbt, Matillion, and Python.
- Integrate data from Epic Clarity/Caboodle, APIs, third-party vendors, and enterprise systems.
- Collaborate with Product Owners, BSAs, and Data Architects to deliver scalable data solutions.
- Implement data quality, monitoring, observability, and automated validation frameworks.
- Apply AI-driven techniques for anomaly detection, schema drift identification, and intelligent data processing.
- Optimize Snowflake performance, scalability, and cost efficiency.
- Prepare curated datasets for analytics and machine learning initiatives.
- Support CI/CD, source control, and development automation practices.
Required Qualifications
- Bachelor's degree or equivalent experience.
- 2+ years of data engineering and ETL/ELT development experience.
- Hands-on experience with Snowflake and advanced SQL.
- Experience with dbt, Matillion, or similar data transformation tools.
- Experience building cloud-based data pipelines.
- Knowledge of AI/ML concepts related to data preparation and feature engineering.
- Experience with Git, CI/CD, APIs, and third-party data integrations.
Knowledge, Skills & Abilities
- Strong analytical, problem-solving, and communication skills.
- Ability to optimize complex data pipelines and troubleshoot data issues.
- Strong attention to detail and ability to work independently or collaboratively.
- Knowledge of healthcare data governance and HIPAA requirements.
- Ability to communicate complex technical concepts to business stakeholders.
- Curiosity and willingness to adopt emerging AI and data technologies.