Refinery Engineer

The Senior Data Engineer is responsible for the design, governance, and ongoing evolution of the organization's enterprise data environment. This role provides leadership in data governance, data architecture, integration, quality, analytics enablement, and AI readiness. Working across clinical, operational, financial, HR, and technology domains, the role ensures organizational data is trusted, secure, accessible, and structured to support decision-making, regulatory compliance, operational excellence, and emerging technologies such as Artificial Intelligence (AI).

The position serves as the organization's senior technical expert on data management practices and acts as a strategic partner to business and technology leaders using technical expertise to create a data environment that supports our team.

• This position offers a competitive compensation range. The salary range is $ to $, and placement within the range will be determined in accordance with company policies and procedures, as well as the candidate’s knowledge, skills, qualifications, and relevant experience.
• Comprehensive health and dental benefits
• Other employment perks such as Employee Assistance Program, Perkopolis, Rewards Points
• Inspiring leadership and opportunities for professional growth
• Rewarding and meaningful work in healthcare

• Lead the organization's Data Governance framework through the Data Governance Council,establishing standards for data ownership, stewardship, quality, access, and lifecycle management.
• Ensure the secure and compliant management of sensitive information, including Personal Health Information (PHI) and Personally Identifiable Information (PII).
• Develop and maintain data governance processes, policies, standards, and controls that support privacy, security, compliance, and organizational objectives.
• Promote accountability and consistent data management practices across all business, operational, and clinical functions.
• Support governance frameworks that enables the responsible and ethical use of data and AI technologies.

• Design, develop, and maintain the organization's enterprise data platform and data warehouse architecture.
• Establish and maintain data models, structures, standards, and integration patterns that support reporting, analytics, operational processes, and strategic decision-making.
• Define the long-term data architecture roadmap, ensuring solutions are scalable, secure, sustainable, and aligned with organizational priorities.
• Evaluate and recommend data technologies, platforms, and architectural approaches that improve organizational capabilities.
• Ensure data architecture supports future growth, advanced analytics, automation, and AI initiatives. DATA INTEGRATION, ENGINEERING AND MODELING
• Design, develop, and maintain enterprise data pipelines that integrate data from clinical, financial, operational, HR, and third-party systems.
• Develop and support ETL/ELT processes that transform complex source data into trusted and reusable organizational datasets.
• Create and maintain data models that improve consistency, usability, and performance across reporting and analytics solutions.
• Implement automated monitoring, validation, and error-handling processes to ensure data reliability and integrity.
• Maintain scalable, maintainable, and high-performing data solutions that support evolving business need

• Establish enterprise standards and processes for data quality management, validation, monitoring, and issue resolution.
• Identify data quality risks, gaps, inconsistencies, and root causes, and collaborate with stakeholders to implement sustainable corrective actions.
• Translate complex healthcare and business data into accurate, reliable, and accessible information assets.
• Develop controls and quality measures that improve trust and confidence in organizational data.
• Foster a culture of data stewardship and continuous improvement across the organization.

• Develop and maintain trusted datasets that support reporting, dashboards, analytics, quality improvement initiatives, and performance measurement.
• Partner with business, clinical, operational, and technology leaders to understand information needs and deliver scalable data solutions.
• Act as a senior advisor on data governance, architecture, integration, analytics, and information management…