Senior Data Engineer - AI Platforms

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. As a Senior Data Engineer, you will design and build scalable data platforms and pipelines that power AI and analytics use cases, focusing on healthcare data and interoperability standards.

Responsibilities:

• Design and build scalable data pipelines (ETL/ELT) using modern data engineering frameworks
• Develop and optimize batch and real-time data processing systems
• Build and maintain data integration workflows across multiple systems and sources
• Ensure data quality, integrity, and reliability across the data lifecycle
• Work with large-scale structured and semi-structured datasets
• Optimize data pipelines for performance, scalability, and cost efficiency
• Collaborate with stakeholders to translate business needs into technical solutions
• Design and implement data models to support analytics and AI use cases
• Support healthcare data ingestion and transformation, including interoperability standards
• Maintain best practices for CI/CD, testing, and monitoring of data pipelines

Requirements:

• 7+ years of experience in Data Engineering or Data Platform development
• Strong hands-on experience with at least one of: Python, SQL, PySpark
• Experience working with at least one of the following data platforms: Snowflake, PostgreSQL, BigQuery, Amazon Redshift
• Experience building and maintaining data pipelines using one or more of: ETL / ELT frameworks, dbt, Dataflow, Dataproc, EMR, or AWS Glue
• General data pipeline / data integration frameworks
• Strong SQL expertise (joins, window functions, performance tuning)
• Experience working with large-scale data processing systems
• Experience working within Healthcare domain, specifically: Healthcare providers or payer systems, Healthcare datasets (EHR/EMR)
• Familiarity with healthcare interoperability standards such as: HL7 (v2 preferred), FHIR (nice to have)
• Experience working with systems such as: Epic (preferred), Other clinical or healthcare data platforms
• Experience with cloud platforms (AWS, GCP, or Azure)
• Familiarity with real-time or streaming data architectures
• Exposure to modern data stack tools and best practices
• Experience with data governance, data quality, and observability tools
• Strong communication skills and experience working with cross-functional teams