Senior Data Specialist - Commercial SME

Role: Commercial SME Type: Contract Location: New Jersey– Hybrid role Key Responsibilities: • Commercial Domain Expertise: • Act as the primary SME for commercial operations, providing insights and leadership in Sales, Marketing, Incentive Compensation (IC), Patient Data Management, Longitudinal Access and Adjudication Data (LAAD), and Claims. • Guide the design, implementation, and optimization of business processes in the commercial functions, ensuring alignment with company objectives and industry standards. • Translate complex commercial business needs into actionable data solutions, ensuring that technology strategies align with business priorities. • Data Engineering & Technical Leadership: • Must have experience in BI Reporting tools. • Lead the development and deployment of data engineering solutions within the Azure ecosystem, utilizing tools such as Azure Data lake, Azure Databricks, to manage large datasets effectively. • Design and implement scalable, secure, and efficient data pipelines that integrate diverse commercial datasets from Sales, Marketing, Claims, Patient Data, and LAAD. • Collaborate with cross-functional teams (including IT, Data Science, and Business Operations) to ensure seamless integration of data engineering solutions across various commercial and business functions. • Apply expertise in SQL, Python, and other data engineering languages to build and manage data pipelines and models. • Life Sciences & Industry Knowledge: • Deeply understand the Life Sciences sector, particularly commercial functions, including sales performance analytics, marketing effectiveness, incentive compensation, patient-centric data, and claims management. • Work closely with business stakeholders to define KPIs, performance metrics, and reporting strategies for Sales, Marketing, and Claims processes, driving actionable insights for business decisions. • Ensure compliance with industry regulations (e.g., HIPAA, GDPR) in all data management and analytics activities related to commercial operations. • Provide functional leadership on the management and utilization of Longitudinal Access and Adjudication Data (LAAD), ensuring the successful integration of longitudinal data to support patient-centric commercial activities. • Collaboration & Cross-Functional Support: • Serve as the key liaison between business and technical teams, ensuring that data solutions meet business requirements and deliver on key commercial goals. • Collaborate with IT teams to ensure data infrastructure supports business intelligence, reporting, and analytics needs, optimizing performance, availability, and security. • Lead the design of business intelligence solutions, including dashboards and reports, for senior commercial leadership, helping them drive data-informed decisions. • Data Governance and Strategy: • Contribute to the development of data governance frameworks for commercial data, ensuring high data quality, security, and compliance standards are met. • Help drive strategic initiatives related to data management, standardization, and integration across commercial functions. • Provide guidance on best practices for data-driven decision-making and ensure alignment with both business and regulatory requirements. Required Skills & Qualifications: • Experience: • 8+ years of experience in commercial operations within the Life Sciences industry, with expertise in areas like Sales, Marketing, Incentive Compensation (IC), Patient Data, LAAD, and Claims. • 5+ years of experience in Data Engineering, including hands-on experience with cloud platforms (preferably Azure), and a strong background in managing and analyzing large datasets. • Proven track record of developing and deploying data solutions that support commercial business functions in Life Sciences. • Technical Expertise: • Proficiency in Azure Data Services (e.g., Azure Data Lake, Azure SQL, Azure Databricks, Azure Synapse). • Expertise in SQL, Python, or other relevant data engineering languages for building data models, pipelines, and reports. • Strong understanding of data warehousing, ETL processes, and data lake architectures. • Familiarity with business intelligence tools such as Power BI, Tableau, or similar platforms for visualization and reporting. • Domain Knowledge: • Extensive understanding of Life Sciences commercial functions, including Sales, Marketing, Incentive Compensation (IC), Claims, Patient Data Management, and Longitudinal Access and Adjudication Data (LAAD). • Ability to translate complex Life Sciences business processes into technical requirements and solutions. • Knowledge of industry regulations (e.g., HIPAA, GDPR, 21 CFR Part 11) and compliance considerations in managing commercial data