Remote - Commercial SMEContract (Only W2- , Hybrid)

Role : Commercial SME Location : Atlanta, GA Hybrid) Contract (Only W2) 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 : Lead the development and deployment of data engineering solutions within the Azure ecosystem, utilizing tools such as Azure Data Lake, and 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.