Overview
On Site
Full Time
Skills
Optimization
IT Management
Data Science
Business Operations
Claims Management
KPI
Performance Metrics
Collaboration
Analytics
Dashboard
Leadership
Data Governance
Data Quality
Decision-making
Cloud Computing
SQL Azure
Databricks
Microsoft Azure
SQL
Python
Data Engineering
Data Warehouse
Extract
Transform
Load
Data Lake
Business Intelligence
Microsoft Power BI
Tableau
Visualization
Reporting
Sales
Marketing
Internal Communications
IC
Integrated Circuit
Data Management
Life Sciences
Business Process
HIPAA
Regulatory Compliance
Management
Job Details
Lead Data Engineering SME- Commercial Operations
Atlanta GA (100% onsite)
6 Months & Extension
Key Responsibilities:
Commercial Domain Expertise:
Experience:
Atlanta GA (100% onsite)
6 Months & Extension
Key Responsibilities:
Commercial Domain Expertise:
- ct 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.
- Lead the development and deployment of data engineering solutions within the Azure ecosystem, utilizing tools such as Azure Datalake, 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.
- pply expertise in SQL, Python, and other data engineering languages to build and manage data pipelines and models.
- 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.
- 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.
- 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.
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 analysing large datasets.
- Proven track record of developing and deploying data solutions that support commercial business functions in Life Sciences.
- 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.
- Extensive understanding of Life Sciences commercial functions, including Sales, Marketing, Incentive Compensation (IC), Claims, Patient
- Data Management, and Longitudinal Access and Adjudication Data (LAAD).
- bility 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.
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