Senior Data Platform Engineer, Commercial

Location:  This position may be performed remotely, but requires the flexibility and willingness to travel as needed.

The Opportunity

Praxis is expanding the engineering team behind its commercial data foundation. We’re looking for a Senior Data Platform Engineer, Commercial to build and maintain the pipelines, models, and integrations that give commercial teams dependable data for execution and decision-making. 

This is a hands-on engineering role for someone who can translate business needs into well-engineered, tested, and maintainable data products. You’ll work directly with commercial data owners and technical partners to turn approved business definitions into trusted data, while taking ownership for data quality, operational reliability, documentation, and ongoing support. 

You’ll partner closely with the Senior Snowflake Platform Engineer on production delivery and support. Your primary focus will be commercial data pipelines, transformations, models, and integrations; both engineers will troubleshoot SQL and Python, maintain operational documentation, and cross-train to provide reliable coverage for critical workloads. 

Primary Responsibilities

• Design and maintain scalable ETL/ELT pipelines and transformations across Snowflake Bronze, Silver, and Gold layers. 
• Integrate data from CRM, field activity, marketing, and external sources, and manage changes with application owners and data providers. 
• Partner with commercial data owners to translate requirements and definitions into consistent, reusable data models. 
• Build automated checks for data completeness, freshness, accuracy, and schema changes, and resolve issues before they reach users. 
• Monitor workloads, troubleshoot failures, support reprocessing and backfills, and implement lasting fixes to recurring issues. 
• Build reliable data products for analytics, reporting, Streamlit, and AI-enabled use cases while maintaining appropriate access and privacy controls. 
• Use strong engineering practices, automation, documentation, and knowledge sharing so critical workloads can be supported across the team. 

Qualifications and Key Success Factors

• 7+ years of relevant experience in data engineering, analytics engineering, or related disciplines—or equivalent demonstrated depth—with hands-on experience delivering and supporting production Snowflake workloads.  
• Strong SQL and Python skills, including experience building maintainable pipelines, transformations, data-quality checks, and operational automation.  
• Strong foundation in analytical or dimensional data modeling, including reusable semantic models and consistent implementation of business definitions across data products.  
• Hands-on experience integrating APIs, files, or shared datasets and managing schema changes, incremental processing, reconciliation, reprocessing, and recovery.  
• Experience with modern transformation practices and tooling such as dbt or equivalent approaches, supported by automated data-quality and regression testing.  
• Strong Git and collaborative development practices, including peer review, controlled environment promotion, production monitoring, and incident resolution.  
• Ability to work directly with non-technical stakeholders, ask the questions needed to clarify ambiguous requirements, and validate that delivered data supports the intended business use.  
• Bachelor’s degree in a relevant technical field or equivalent practical experience. 
• The physical and mental requirements of our roles include but are not limited to regular use of a computer, devices or other office equipment, clear communication, and occasional movement. You'll need comfort with screen work, basic hand coordination, and focus. Reasonable accommodations may be made to enable individuals with disabilities to perform these functions.