Senior Data Engineer

CarePartners•Waterloo, ON

11d•CA$100,000 - CA$120,000•Remote

About The Position

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.

Requirements

A bachelor’s degree, or equivalent practical experience in data engineering, information systems, health informatics, or a related field.
At least 7 years experience in data-based roles including time as a Data Engineer, Analytics Engineer, Data Warehouse Engineer, or similar roles.
Superb SQL skills and experience working with relational databases.
Experience building ETL or ELT pipelines from source systems into a data warehouse, database, or cloud data platform.
Experience with Python or another programming language used for data processing.
In depth understanding of data modeling, data warehouse design (such as medallion architectures), and organizing data for analytics and reporting.
Ability to work with incomplete, or inconsistent data and create solutions.
Comfortable working in an environment where processes are still being built.
Strong communication skills and the ability to explain technical work to non-technical partners.
Ability to create and maintain clear data definitions, business rules, and documentation.
Ability to work well with a team of data analysts and provide indirect leadership, guidance and mentorship.
Travel within Ontario and the ability to work non-traditional and on-call hours is a requirement
Valid driver's license, own vehicle and appropriate insurance
Clear Criminial Record

Nice To Haves

Experience working with healthcare (ideally home healthcare) data or in a healthcare, clinical, or related environment is preferred.
In depth understanding of healthcare privacy and security requirements, including responsible handling of PHI is preferred.
Experience with healthcare data standards such as HL7, FHIR, or ICD is preferred.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with data platforms such as Snowflake, Databricks, or Azure Synapse.
Experience supporting business intelligence tools such as Power BI, Tableau, Looker, or similar platforms.
Experience with data governance practices, including data quality, documentation, access controls, privacy, data ownership, and secure handling of healthcare data.

Responsibilities

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.
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 needs.
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 initiatives.
Translate complex technical concepts into clear and meaningful information for both technical and non-technical stakeholders.
Support organizational efforts to become increasingly data-driven through accessible and trusted information.
Lead the development of the foundational data capabilities required to support Artificial Intelligence (AI), machine learning, automation, and advanced analytics initiatives.
Ensure data used for AI solutions is governed, secure, high-quality, and compliant with privacy and regulatory requirements.
Help evaluate emerging AI, analytics, and data technologies and provide recommendations to support organizational strategy and innovation.
Support the organization's responsible adoption of AI through strong governance, transparency, and risk management practices.
Maintain comprehensive documentation of data sources, lineage, transformations, business definitions, architecture, governance processes, and technical standards.
Establish documentation and operational standards that support transparency, maintainability, and long-term sustainability of the data environment.
Drive continuous improvement initiatives that improve data reliability, scalability, security, and operational effectiveness.
Promote best practices for data management, governance, analytics, and AI readiness across the organization.
Contribute to the ongoing advancement of the organization's data maturity and information management capabilities.