Data Engineer
2 weeks ago
What sets us apart? Our cutting-edge, API-first, UI-agnostic, end-to-end provider network management platform automates licensing, enrollment, credentialing, and network monitoring like never before. With direct integrations into hundreds of primary sources, we have an unbeatable advantage in enhancing visibility into the entire provider network management process. Plus, our team brings over 25+ years of combined experience building provider data systems at Oscar Health, and we're backed by top-tier VC firms who share our bold vision of creating a one-of-a-kind healthcare cloud that eliminates friction surrounding provider data.
But it's not just about the technology; it's about the people behind it. At Certify, we foster a meritocratic environment where every voice is heard, valued, and celebrated. We're founded on the principles of trust, transparency, and accountability, and we're not afraid to challenge the status quo at every turn. We're looking for purpose-driven individuals like you to join us on this exhilarating ride as we redefine healthcare data infrastructure. Requirements
- Good understanding of SQL and data analysis
- Have utilized GenAI or basic understanding GenAI/LLM tools
- Basic knowledge of Python for data processing
- Awareness of ETL concepts and workflow tools like Airflow or dbt
- Good understanding of programming concepts and algorithms.
- Exposure to cloud platforms (AWS, GCP, or Azure)
- Interest in data pipelines, orchestration, and data quality
- Strong analytical and problem-solving mindset
- Pursuing or recently completed a degree in Computer Science, Data Engineering, or related field
- (Optional) Experience through academic projects or open-source contributions
- Support the design and development of data pipelines for ingestion, transformation, and storage
- Assist in building and maintaining data models for analytics and reporting
- Work on cleaning, validating, and enriching datasets
- Collaborate with engineers, analysts, and scientists to understand data requirements
- Document data flows, schema updates, and technical processes
- Contribute to automation and performance optimization tasks
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