Data Analyst II, Incentive Compensation

Responsibilities

Sales Crediting Platform Ownership

• Own day-to-day operations and continuous enhancement of the in-house Sales Crediting Platform, ensuring accurate, timely and reliable processing of sales crediting activities.
• Translate business requirements, sales crediting rules and Incentive Compensation processes into technical requirements and implement scalable solutions.
• Develop, maintain and optimize data pipelines, transformations, business rules and validation processes supporting sales crediting.
• Monitor platform performance, identify data/process issues, perform root-cause analysis and drive timely resolution of production issues.
• Partner with Incentive Compensation stakeholders to understand changes in business rules, field force structures, products, territories and crediting methodologies and translate these into platform enhancements.
• Establish robust data quality, validation and reconciliation frameworks to ensure accuracy and completeness of sales crediting outputs.
• Support recurring Incentive Compensation cycles and ensure operational readiness, including testing, validation, deployment and post-production monitoring.
• Identify opportunities to automate manual processes and improve platform efficiency, scalability and reliability.

Data Engineering Analytics

• Build and maintain scalable data pipelines to ingest, transform, validate and integrate data from multiple internal and external sources.
• Work with large and complex datasets using SQL, Python and Databricks to perform data transformation, analysis and troubleshooting.
• Develop reusable data processing and analytical solutions that improve efficiency, reduce manual intervention and enhance data quality.
• Collaborate with Data Analytics and IT teams to develop and enhance data architecture, pipelines, analytical tools and platform capabilities.
• Perform data profiling, reconciliation, anomaly detection and root-cause analysis across multiple data sources.
• Develop dashboards, reports and analytical outputs where required to monitor sales crediting performance, data quality and operational KPIs.

Technology, Automation AI

• Identify and implement opportunities to leverage AI, GenAI, machine learning, automation and emerging technologies to improve Incentive Compensation and sales crediting processes.
• Explore practical applications of AI for areas such as data validation, anomaly detection, issue identification, process automation, documentation and operational insights.
• Stay current with emerging data engineering, AI and analytics technologies and assess their potential application within the Incentive Compensation ecosystem.
• Continuously challenge existing processes and identify opportunities to make the platform more automated, scalable, intelligent and user-friendly.

Stakeholder Project Management

• Partner closely with Incentive Compensation, Commercial, IT, Data Analytics and other cross-functional stakeholders to understand requirements and deliver solutions.
• Communicate complex technical and data concepts clearly to non-technical stakeholders.
• Manage multiple enhancements, operational priorities and projects while maintaining high standards of quality and execution.
• Lead or contribute to platform enhancement initiatives from requirements gathering through development, testing, deployment and stabilization.
• Collaborate with vendor/partner teams where required and ensure effective knowledge transfer and delivery.

Process Knowledge Management

• Develop and maintain process documentation, SOPs, technical documentation, data dictionaries, process maps, business requirements and validation frameworks.
• Establish best practices around data engineering, testing, quality control, change management and platform operations.
• Build strong domain knowledge of Incentive Compensation, sales crediting, commercial operations and relevant business processes.
• Become a subject matter expert on the Sales Crediting Platform and serve as a key point of contact for platform-related questions and issues.

Skills Competencies

Technical / Data Engineering

• Strong hands-on experience with SQL and Python.
• Strong understanding of data engineering concepts including ETL/ELT, data pipelines, data transformation, data quality, data validation and data integration.
• Experience working with Databricks and/or similar cloud-based data platforms.
• Experience working with large, complex datasets and multiple data sources.
• Understanding of data architecture, data modeling and scalable data processing.
• Experience with APIs, cloud technologies, workflow orchestration or CI/CD is a plus.
• Experience with BI/visualization tools such as Power BI, Tableau or similar is an advantage.

AI Emerging Technology

• Strong interest in and practical understanding of AI/GenAI and emerging data technologies.
• Demonstrated ability to identify opportunities to apply AI or automation to improve business processes.
• Experience building or experimenting with AI/GenAI solutions, LLMs, intelligent automation or machine learning is a strong plus.
• Curiosity and willingness to learn new technologies quickly is critical for this role.

Business Analytical Skills

• Strong analytical and problem-solving skills with the ability to break down complex business problems into structured technical solutions.
• Ability to understand business rules and translate them into data logic and scalable technical implementations.
• Strong attention to detail, particularly given the financial and field-force impact of sales crediting and Incentive Compensation.
• Ability to investigate ambiguous data issues, identify root causes and develop sustainable solutions.
• Strong business acumen and ability to understand the "why" behind requirements rather than simply executing technical specifications.

Collaboration Communication

• Strong written and verbal communication skills with the ability to interact effectively with both technical and business stakeholders.
• Ability to work independently while collaborating effectively across a matrix organization.
• Strong ownership mindset with the ability to take accountability for platform performance and deliverables.
• Comfortable working in a fast-paced environment with changing priorities.
• Quick learner with high intellectual curiosity and a continuous improvement mindset.

Experience Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, Engineering, Information Technology, Business Analytics, Statistics, Mathematics or a related discipline.
• 3-6 years of experience in data engineering, data analytics, business intelligence, data platforms or a similar technical role.
• Experience working with Databricks or similar modern data platforms.
• Experience building or managing data pipelines and working with large datasets.
• Experience with cloud data platforms such as Azure, AWS or GCP is an advantage.
• Experience with AI/GenAI, machine learning, automation or modern analytics technologies is strongly preferred.
• Experience in pharmaceutical/biopharma commercial operations, Incentive Compensation, sales