Strong programming skills in Python, SQL, Java, or Scala.
Hands-on experience with Snowflake, including Snowpark, Streams & Tasks, Dynamic Tables, and Secure Data Sharing.
Knowledge of healthcare standards such as HL7, FHIR, CCD/CCDA, ICD and CPT.
Experience in ETL/ELT pipelines, data integration, data validation, and data warehousing.
Experience with REST APIs, JSON/XML, microservices, and cloud platforms (AWS/Azure/GCP).
Familiarity with Git, CI/CD, automated testing, and DevOps practices.
Understanding of healthcare EHR/EMR systems such as Epic and Cerner.
Exposure to Power BI/Tableau and AI-driven solutions is an added advantage.
Key Responsibilities:
Strong experience in Snowflake, SQL, Python, and Snowpark.
Hands-on experience with Snowflake Streams, Tasks, Dynamic Tables, and Secure Data Sharing.
Healthcare domain knowledge, including EHR/EMR, patient, provider, claims, and clinical data.
Knowledge of healthcare standards such as HL7, FHIR, CCD/CCDA, ICD, and CPT.
Experience in ETL/ELT pipelines, data integration, transformation, and validation.
Experience with AWS/Azure, Git, and CI/CD.
Exposure to DBT, Power BI, or Tableau.
Knowledge of HIPAA compliance, PHI handling, and healthcare data security.
Strong understanding of data modeling, performance tuning, and cost optimization.
Lead the design, development, and maintenance of production-grade data engineering and analytics services, driving enterprise-scale data solutions and AI-powered insights.
Responsibilities
Architect, deploy, and maintain production-grade Python microservices, serverless components, batch workers, web services, and shared core libraries
Engineer RESTful interfaces and application integrations for dataset capabilities
Construct backend infrastructure powering AI analytics solutions
Author clean, resilient codebase with comprehensive test suites and CI/CD pipelines
Safeguard system configuration and secrets
Requirements
Bachelor’s degree in Computer Science or related field
Senior Data Engineer with deep expertise in AWS and Snowflake, responsible for designing, developing, and deploying scalable, secure, cloud-native data solutions that enable data-driven decision making.
Compensation
The pay range for this position is $109700.00 - $164500.00/yr.
Responsibilities
Actively involved in requirement gathering workshops and translating functional requirements into technical solutions
Participated in architectural discussions to design and develop secure, scalable, cost-optimized data engineering solutions
Designed and implemented modern data platform architectures using AWS-native services and Snowflake
Developed scalable data ingestion, transformation, and orchestration pipelines using AWS services
Designed high-performance Lakehouse and Warehouse models following AWS Well Architected Framework guidelines
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or related field
A Senior Solution Engineer role at the intersection of data, AI, and complex enterprise architecture, working with sales teams and partners to deliver demonstrations and proof of concepts.
Locations (2)
North Carolina, United States
South Carolina, United States
Compensation
$220,000 - $288,000 OTE (On Target Earnings = Base Salary + Commission/Quota)
Responsibilities
Present Snowflake's Data Cloud vision to data engineering leaders, analytics teams, data scientists, and executive stakeholders at prospects and customers
Lead hands-on technical discovery to map a customer's existing data architecture — pipelines, warehouses, lakehouses, governance gaps — and design a Snowflake-native path forward
Build and deliver tailored demos and proof of concepts across Snowflake's full data platform: data engineering (Snowpark, Dynamic Tables, Snowpipe), AI/ML (Cortex AI, ML model registry), and data sharing (Data Clean Rooms, Marketplace listings)
Guide customers through modern data architecture patterns including Data Mesh, Data Lakehouse, real-time streaming pipelines, and unified governance frameworks
