Senior Data Platform Engineer, Commercial

Role overview

A clinical-stage biopharmaceutical organization is expanding the engineering team behind its commercial data foundation and is hiring a Senior Data Platform Engineer 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 focused on translating business needs into well-engineered, tested, and maintainable data products, with close partnership alongside commercial data owners and technical peers. The position emphasizes ownership of data quality, operational reliability, documentation, and ongoing support.

Responsibilities

- Design and maintain scalable ETL/ELT pipelines and transformations across Bronze, Silver, and Gold layers in Snowflake. - Integrate data from CRM, field activity, marketing, and external sources, and coordinate schema 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 drift, resolving issues before they reach end users. - Monitor production workloads, troubleshoot failures, support reprocessing and backfills, and implement durable fixes to recurring problems. - Deliver reliable data products for analytics, reporting, dashboarding, and AI-enabled use cases while enforcing appropriate access and privacy controls.

Requirements

- 7+ years of relevant experience in data engineering, analytics engineering, or related disciplines, with hands-on delivery and support of production Snowflake workloads. - Strong SQL and Python skills, including building maintainable pipelines, transformations, data-quality checks, and operational automation. - Solid foundation in analytical or dimensional data modeling, including reusable semantic models and consistent application of business definitions across data products. - Experience integrating APIs, files, or shared datasets, and managing schema changes, incremental processing, reconciliation, reprocessing, and recovery. - Familiarity with modern transformation tooling such as dbt or comparable approaches, supported by automated data-quality and regression testing. - Strong Git and collaborative engineering practices, including peer review, controlled environment promotion, production monitoring, and incident resolution. - Bachelor's degree in a relevant technical field or equivalent practical experience, with the ability to clarify ambiguous requirements directly with non-technical stakeholders.

Benefits and work setup

- Remote-eligible with flexibility and willingness to travel as needed. - Annualized base salary range of $140,000–$160,000 USD. - 99% of premiums covered for medical, dental, and vision plans; company-paid life insurance, AD&D, and disability coverage with voluntary plan options. - Dollar-for-dollar 401(k) match up to 6%, long-term stock incentives, and an employee stock purchase plan. - Discretionary quarterly bonus, flexible wellness benefit, generous PTO, paid holidays, and company-wide shutdowns.