Senior Data Engineer – AI Platforms

🕒 April 23

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Quantiphi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

📚 Education

💰 Series A on 2019-12

Artificial Intelligence • Enterprise • Education

Quantiphi is a leading AI-first digital engineering company that leverages a decade of industry expertise to empower businesses through scalable, secure, and adaptable AI solutions. By integrating cutting-edge technology with real-world applications, Quantiphi transforms organizations across various sectors including healthcare, finance, education, and retail. Their services span AI applications, data analytics, cloud infrastructure modernization, and custom AI implementations. Quantiphi partners with technology giants like AWS, Google Cloud, NVIDIA, and others to drive AI adoption and deliver transformational opportunities for enterprises.

📋 Description

• As a Senior Data Engineer, you will design and build scalable, production-grade data platforms and pipelines that power AI and analytics use cases. • This role is highly hands-on and sits at the intersection of data engineering, AI enablement, and cloud platforms. • You will work closely with clients and internal stakeholders to build modern data ecosystems, with a strong focus on healthcare data and interoperability standards. • 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 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 • 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)

🏖️ Benefits

• Make an impact at one of the world’s fastest-growing AI-first digital engineering companies. • Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues. • Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines. • Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.