Job Description

Data Engineer Job Description ================================= Position Summary -------------------- The Data Operations Engineer plays a critical role in managing and optimizing how Alora Pharmaceutical interacts with both on-site and cloud-based data systems, including data warehouses, lakes, Master Data Management (MDM), Customer Master, and analytical tools. This individual ensures data is accurate, accessible, and effective for downstream uses such as reporting, analytics, and decision-making. The role collaborates with internal and external stakeholders to address data system issues, define priorities, and continuously improve data processes. The Data Operations Engineer will report to the Manager, Data Engineering and work closely with the Senior Director, Sales Operations. Key Responsibilities ------------------------

• Collect, integrate, and transform data from multiple sources into curated datasets for downstream analysis and visualization.
• Design and maintain scalable, reusable data pipelines to support reporting and analytics functions.
• Identify and communicate data quality issues and limitations; implement and maintain data quality checks and improvements (Data Quality Roadmap).
• Analyze large, complex datasets to extract insights and trends that drive strategic business decisions.
• Develop code that is efficient, reusable, and well-documented for sustainable data engineering practices.
• Design data outputs suitable for different delivery methods (e.g., dashboards, reports, BI tools).
• Collaborate with business stakeholders and data acquisition teams to define and access the necessary data attributes from source systems.
• Interpret source and target system data models (e.g., Commercial Data Warehouse and Enterprise Data Backbone).
• Build and maintain robust ETL processes for ingestion, transformation, and loading of large-scale datasets.
• Define and implement data engineering best practices for transformation, integrity, testing, and documentation.
• Develop and maintain technical metadata and a comprehensive data catalog to support data discovery and governance.
• Perform root cause analysis on data quality and flow issues in collaboration with IT and third-party data providers.
• Define priorities for resolving data-related issues and communicate effectively across stakeholders.
• Support data systems roadmap development aligned with organizational strategy.
• Monitor and refine complex data management processes (e.g., mastering, matching) to ensure end-to-end data integrity.
• Act as a technical leader and mentor within the data engineering team, promoting collaboration and continuous improvement.

• Bachelor’s degree in Computer Science, Data Analytics, Information Systems, or a related field.
• 3+ years of experience in business analytics or data engineering, preferably within the life sciences industry.
• Strong knowledge of SQL (preferably MS SQL), and experience with visualization tools such as Power BI or Tableau. Knowledge of Orchestrated Analytics is a plus.
• Familiarity with pharmaceutical data sources (e.g., IQVIA, Symphony, DRG, MMIT, OneKey), CRM systems, and MDM platforms.
• Experience with data warehousing and cloud-based architectures.
• Vendor management experience and the ability to navigate third-party partnerships effectively.
• Strong analytical, organizational, and prioritization skills with the ability to manage multiple tasks and stakeholders.
• Excellent verbal and written communication skills; strong team collaboration and interpersonal skills.
• Demonstrated success in leading projects and implementing process improvements.
• High ethical standards with the ability to remain impartial and uphold data governance policies.
• Experience working with large datasets and third-party hosted data environments.
• Working knowledge of data architectures and data analysis workflows.
• Familiarity with machine learning algorithms, advanced Excel proficiency, and prior experience in healthcare or pharma is an asset.

• Location: Alpharetta, GA
• Reports To: Manager, Data Engineering
• Travel: Minimal, as required for collaboration or vendor meetings

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