Senior Data Platform Engineer, Commercial
Praxisprecisionmedicines · United States - Remote
About this role
**Senior Data Platform Engineer, Commercial — Praxis Precision Medicines** **Location**: This position may be performed remotely, but requires 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 translating 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 owning **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**; 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 **completeness, freshness, accuracy, and schema changes**; 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**, maintaining appropriate access and privacy controls. - Apply strong engineering practices: **automation, documentation, and knowledge sharing** to support critical workloads across the team. --- ## Qualifications and Key Success Factors - **7+ years** of relevant experience in data engineering/analytics engineering (or equivalent), with hands-on delivery and support of **production Snowflake workloads**. - Strong **SQL and Python** skills, including maintainable pipelines, transformations, data-quality checks, and operational automation. - Strong foundation in **analytical/dimensional data modeling**, including reusable semantic models and consistent implementation of business definitions. - Hands-on experience integrating **APIs, files, or shared datasets**, managing schema changes, incremental processing, reconciliation, reprocessing, and recovery. - Experience with modern transformation practices and tooling such as **dbt** (or equivalent), supported by automated data-quality and regression testing. - Strong **Git** and collaborative development practices (peer review, controlled environment promotion, production monitoring, incident resolution). - Ability to work with non-technical stakeholders: ask clarifying questions and validate delivered data supports intended business use. - Bachelor’s degree in a relevant technical field (or equivalent practical experience). - Ability to perform role requirements (regular computer/device use, clear communication, occasional mo
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