Develop expertise in the organization’s data landscape and customer architectures to provide technical oversight during implementation
Support customer onboarding and ensure smooth ingestion of sponsor-specific data sources
Collect and validate source data specifications, guide dataset preparation, and map customer data to internal standards
Configure, test, and maintain API integrations; gather requirements, support upgrades, and update integrations post-implementation
Review customer data quality, advise on notifications, and ensure reliable data flow
Establish best practices for data exchange, monitoring, troubleshooting, and regulatory compliance (HIPAA)
Perform root-cause analysis and lead resolution of integration issues
Collaborate with IT, business units, vendors, and engineering teams to implement integration best practices
Drive continuous improvement through optimized delivery playbooks, checklists, and automation tools
Maintain a commercial focus, delivering value to customers while supporting change initiatives, product releases, and cross-functional priorities

Proven experience delivering technical data integrations across multiple systems and organizations
Knowledge of clinical trial data standards and terminologies (CDISC/USDM)
Strong proficiency in SQL and data manipulation (Python/R), with experience in ETL tools, CLI, and cloud platforms (AWS)
Experience with enterprise CRM systems (e.g., Salesforce) and modern data warehouses
Solid understanding of data modeling, flows, and integration patterns; skilled in troubleshooting complex issues
SaaS experience supporting enterprise customers and managing end-to-end integrations
Strong analytical, problem-solving, and data quality skills
Excellent communication for technical and non-technical stakeholders; customer-facing experience
Bachelor’s degree in IT, Computer Science, Data Science, or related field, or equivalent experience
Excellent spoken and written English language skills
A significant advantage would be
Experience in healthcare technology, digital health solutions, or data-intensive SaaS platforms
Knowledge of data privacy and compliance standards (e.g., HIPAA) and their practical application
Familiarity with integration monitoring tools, automation, and customer delivery playbooks
Experience with AI-driven tools or methods to improve data integration efficiency and reduce manual mapping

Data Engineering Lead

Key skills