Manager – Data Engineering & Platforms
- Markham, ON, Canada
$125,000 to $150,000 CAD / year · Full-time
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Job details
- Pay
- $125,000 to $150,000 CAD / year
- Job type
- Full-time
- Experience
- Approximately 5–8+ years of progressive experience in data engineering, data integration, data warehousing, database development or related roles.
- Working hours
- 40 Hours Per Week
- Posting language
- English
- Posted
Original job description
Reference ID: 001-CATC-78
Line of Business: Shared Services
Location: Markham, ON (175 Commerce Valley Dr WMarkham, ON L3T 7P6)
Position Type: Full-Time, Permanent
Vacancy Status: This Posting is for a New Role
Hours: 40 Hours Per Week
Compensation: $125,000 - $150,000
WHAT YOU’LL LOVE ABOUT CATC:
AS A MULTIDISCIPLINARY HEALTHCARE TEAM - TOGETHER, WE:
Compassion – we meet people where they are, ready to help
Accountability – we take responsibility for outcomes
Respect – we work well with others
Excellence – we deliver exceptional experiences to everyone we encounter
- Wellness: Group Benefits Plan for you and your family along with Employee Assistant Programs through TELUS Health, discounted GoodLife fitness memberships, paid time off for vacation, wellness days for illness, and mental health, and bereavement.
- Career Development: Professional Development, including CNO License reimbursement, Lunch & Learn Sessions and access to 100+ courses within the Company’s Learning Management System.
- Preparation for the Future: Retirement Savings Plan (RRSP/DPSP).
- Employee Recognition: Service Recognition Program.
ABOUT THE POSITION:
Canadian Addiction Treatment Centres (“CATC”) is a leading Canadian provider of addiction treatment services, operating a large and growing network of treatment centres, pharmacies and related healthcare services across Canada. CATC is is seeking a Manager, Data Engineering & Platforms to lead the development, operation and continuous improvement of CATC's enterprise data platform.
Reporting to the Director of Information Technology, the Manager will have primary responsibility for CATC's Azure SQL data warehouse and the Python, SQL and dbt-based pipelines, integrations and APIs that connect CATC's operational systems, automation platforms and business applications to the warehouse, including current integrations involving Zapier and Salesforce.
The Manager will work closely with Finance, FP&A, Information Technology, operational leaders and system owners to ensure that reliable, timely and appropriately structured data is available to support financial planning and analysis, management reporting, Power BI analytics and operational decision-making.
This is a hands-on technical leadership position. The successful candidate will combine strong data engineering and data architecture capabilities with an ability to understand business requirements, investigate data problems across source systems, and work collaboratively with business and technical stakeholders to develop sustainable solutions.
YOUR DUTIES AND RESPONSIBILITIES:
Data Integration & Engineering
- Own and maintain the Python, SQL and dbt-based data connections, integrations, APIs and data pipelines between CATC's operational systems and its Azure SQL data warehouse.
- Design, develop, implement and support new data integrations required to meet evolving business and reporting requirements.
- Own and support data integrations between automation platforms and core business systems, including current integrations involving Zapier, Salesforce and related operational data flows.
- Develop and maintain ETL/ELT processes using Python, SQL and dbt to extract, transform and load information from source systems into CATC's data warehouse.
- Work with third-party software providers and internal IT resources to understand available APIs, database structures, data exports and integration options.
- Monitor data pipelines and interfaces for failures, latency, completeness and other issues, and implement appropriate monitoring and exception-handling processes.
- Troubleshoot integration and data-processing issues and perform root-cause analysis to prevent recurring problems.
Data Warehouse & Architecture
- Own the technical operation, maintenance and continuous improvement of CATC's Azure SQL data warehouse.
- Design and maintain scalable data structures, tables, relationships and data models that support financial, operational and analytical requirements.
- Develop and maintain appropriate data architecture standards, including naming conventions, data models, dbt transformation logic and documentation.
- Optimize database structures, queries and data pipelines for reliability, usability and performance.
- Evaluate opportunities to improve CATC's data architecture and recommend appropriate technologies, tools and architectural changes as requirements evolve.
- Maintain appropriate development, testing, change-management and deployment practices for the data environment.
Business Requirements & Analytics Enablement
- Identify the source-system data required to meet new business requirements and determine the appropriate method for capturing, integrating, transforming and storing that information.
- Manage the end-to-end process of introducing new data elements into the data warehouse, from business requirement through source-system identification, integration, modelling, validation and production deployment.
- Advise business stakeholders on data availability, limitations and appropriate use.
- Work with Power BI developers and business analysts to ensure that data warehouse structures and datasets are designed to support effective reporting and analytics.
Data Quality & Operational Process Improvement
- Establish processes to monitor the completeness, accuracy, consistency and timeliness of data entering CATC's data warehouse.
- Investigate data-quality issues and determine whether problems originate in source-system configuration, operational processes, integrations, transformation logic or reporting.
- Work directly with operational business owners to identify and resolve processes that result in missing, inaccurate, inconsistent or late data.
- Develop automated validation, reconciliation and exception reporting wherever practical.
- Help establish clear ownership and accountability for critical business data across CATC.
- Support the development of appropriate data definitions, business rules and documentation for key organizational metrics.
Governance, Security & Documentation
- Ensure data solutions comply with CATC's information security, privacy and access-control requirements.
- Maintain documentation of data sources, integrations, data flows, transformations, tables, business rules and system dependencies.
- Support appropriate controls over changes to production data pipelines and warehouse structures.
- Contribute to CATC's broader data governance, data retention and information-management practices.
- Own and advance CATC's data classification approach, ensuring that sensitive, regulated and business-critical data is appropriately identified, documented and handled across the data environment.
- Develop and maintain data fencing, access segmentation and governance practices that support safe future AI enablement, including appropriate controls over which data can be exposed to AI-enabled tools and workflows.
Technical Leadership & Continuous Improvement
- Serve as CATC's internal technical subject-matter expert for data integration, data engineering and data warehouse architecture.
- Establish technical standards and best practices for CATC's data engineering environment.
- Manage external consultants, vendors and technical resources supporting data engineering initiatives, where required.
- Evaluate opportunities to modernize CATC's data platform, including potential future adoption of Microsoft Fabric or other Azure data technologies where they provide meaningful business value.
- Develop a roadmap for the continued evolution, scalability and reliability of CATC's enterprise data platform.
WHAT YOU’LL NEED TO HAVE:
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering or a related discipline, or equivalent relevant professional experience.
- Approximately 5–8+ years of progressive experience in data engineering, data integration, data warehousing, database development or related roles.
- Strong hands-on experience with Python, SQL and relational database development in a production data environment.
- Experience developing, maintaining and troubleshooting dbt models, transformations and related data-engineering workflows.
- Strong experience designing and maintaining relational databases, enterprise data warehouses and scalable data structures.
- Advanced SQL skills, including data transformation, query optimization, stored procedures and troubleshooting.
- Experience designing and supporting ETL/ELT pipelines and integrating data from multiple source systems, including REST APIs, JSON, database connections and other common application-integration methods.
- Experience managing integrations between automation platforms and enterprise business systems; experience with Zapier, Salesforce or similar platforms would be an asset.
- Experience with Azure SQL or comparable cloud-hosted relational data platforms.
- Knowledge of dimensional modelling, relational data modelling and data warehouse design principles.
- Experience diagnosing and resolving complex data-quality and data-integration issues, including issues that originate in source systems, operational processes, integrations, transformation logic or reporting.
- Demonstrated ability to translate business and reporting requirements into practical technical data solutions.
- Experience supporting Power BI or another enterprise business-intelligence platform, including an understanding of how warehouse design affects reporting performance and semantic models.
- Familiarity with Git, Azure DevOps or similar development, source-control and deployment practices.
- Experience implementing automated data-quality monitoring, validation and reconciliation processes would be an asset.
- Experience with Microsoft Fabric, Azure Data Factory, data lakes or modern lakehouse architectures would be an asset, particularly where relevant to future platform modernization.
- Experience working in healthcare or another environment involving sensitive or regulated information would be an asset.
- Familiarity with Canadian healthcare privacy and information-security requirements would be an asset.
- Experience with data classification, access segmentation, data-governance controls or AI-readiness initiatives would be an asset.
- Strong documentation, communication and stakeholder-management skills, with the ability to work effectively with technical teams and non-technical business leaders.
- Experience managing external development resources, consultants or technology vendors would be an asset.
ABOUT THE COMPANY
Founded in 1995, Canadian Addiction Treatment Centres (CATC) operates three inpatient addiction treatment centres, a national network of more than 70 outpatient substance use disorder treatment clinics and specialty pharmacies in Canada.
CATC delivers services in a supportive, compassionate, and judgment-free environment. We are committed to improving the lives of individuals affected by addiction through a multidisciplinary, evidence-based approach that prioritizes quality care and an exceptional patient experience.
Our outpatient clinics provide walk-in support in person or virtually to enable community-based access to accredited treatment programs. Our CARE teams provide rapid access to a team of medical professionals, pharmacy services and wrap-around supports to engage patients through stabilization and treatment plans that enable patient success in achieving care goals.
Our inpatient treatment centres provide structured, 24/7 medically supported care in a safe and therapeutic environment for individuals who require intensive stabilization and recovery support. Care is focused on building a strong foundation for long-term recovery through accredited, evidence-based programming. Our secure virtual counselling services make care more accessible through flexible, remote connections with qualified professionals.
Please visit www.canatc.ca for more information!
Canadian Addiction Treatment Centres remains an inclusive and equal opportunity employer committed to providing accommodations for all applicants upon request at any stage of the selection process in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code.
More about this job
Responsibilities
The Manager of Data Engineering & Platforms will lead the development, operation, and continuous improvement of the enterprise data platform. This includes managing data pipelines, integrations, and the Azure SQL data warehouse to support financial and operational decision-making.
Requirements
Candidates must have a bachelor's degree in a relevant field and 5-8+ years of progressive experience in data engineering and warehousing. Strong hands-on proficiency in Python, SQL, dbt, and cloud-hosted relational database environments is required.
Skills
- Data Engineering
- Python
- SQL
- Dbt
- Azure SQL
- Data Warehousing
- ETL/ELT
- API Integration
- Data Modeling
- Power BI
- Data Quality
- Data Governance
- Technical Leadership
- Cloud Platforms
- Database Architecture
- Stakeholder Management
Benefits
- Group Benefits Plan
- Employee Assistant Programs
- Discounted GoodLife fitness memberships
- Paid time off
- Wellness days
- Mental health support
- Bereavement leave
- Professional development
- CNO License reimbursement
- Lunch & Learn sessions
- Retirement Savings Plan
- Service Recognition Program
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Management & Leadership
- Software
- Healthcare
Keywords
- Data Engineering
- Azure SQL
- Python
- SQL
- Dbt
- ETL
- ELT
- Data Warehouse
- API
- Zapier
- Salesforce
- Power BI
- Data Modeling
- Data Governance
- Git
- Azure DevOps
- Microsoft Fabric
- Data Quality
- Healthcare
- Information Technology
- Database Management
- Cloud Computing
- Relational Databases
- Business Intelligence
- Data Architecture
- Automation
- API Integration
- Data Pipelines
- Technical Leadership
- Analytics