Data Architect
DUCA View all jobs
- Toronto, ON
- $87,445-120,741 per year
- Permanent
- Full-time
- Positive, un-big bank like service experience delivered through Member-facing staff in branch, on the phone (Member-Connect) and via our Mobile mortgage specialists, Wealth Management advisors and Commercial and Business Banking Account Managers.
- Competitive rates.
- Personalized financial solutions, guidance, and service with the lowest possible fees for both Personal and Business Members.
- Profit sharing among Members.
- Multiple ways to bank-online, mobile app, phone/full-service Member Connect Contact Centre, and, of course, in-branch-DUCA is accessible 24/7
- A community philosophy of “profits with a purpose” culminating in the creation of the DUCA Impact Lab (www.ducaimpactlab.com), a charitable foundation committed to helping the credit challenged and underbanked. This led to DUCA's designation as a B-Corp certified organization, the first ever credit union to receive this global recognition.
- Build and maintain DUCA's enterprise data architecture, including target-state design, standards, and execute on DUCA's modernization roadmap.
- Lead the evolution, expansion, and optimization of the Lodestar data warehouse and related platforms.
- Establish best practices for data modelling, metadata, lineage, and semantic layers across all data domains.
- Collaborate with business and technology leaders to prioritize data ingestion and integration initiatives aligned to DUCA's strategic goals.
- Champion data governance, including data quality standards, ownership frameworks, access controls, and stewardship practices.
- Serve as DUCA's subject matter expert on enterprise data structure, architecture, and analytical tooling.
- Lead cross-functional collaboration between Business Systems Analysts, Data Stewards, and business partners to improve data literacy and maximize the value of enterprise data.
- Design, build, and optimize data ingestion pipelines ensuring reliable, timely, and secure data delivery.
- Oversee data quality processes, observability, monitoring, and controls to ensure trust in core data assets.
- Ensure all architecture and pipelines are documented and maintained in accordance with industry standards.
- Collaborate with system owners to ensure data is integrated seamlessly across platforms.
- Lead the development of dashboards, KPIs, and analytical assets that provide actionable insights for business units and leadership.
- Drive adoption of self-serve analytics through well-structured semantic models and governed data sets.
- Identify and implement opportunities to incorporate Artificial Intelligence to automate analytics workflows, increase efficiency, and enhance decision-making capabilities.
- Act as a partner to business leaders by translating data into insight-supported recommendations.
- Undergraduate degree in Computer Science, Data Science, Engineering, Business Technology, or related field.
- 7+years of progressive experience in data architecture, data engineering, or enterprise analytics.
- Demonstrated experience designing and managing enterprise data warehouses, preferably in a financial services environment.
- Hands-on experience building and maintaining data pipelines, data models, BI solutions, and analytics platforms.
- Experience with AI/ML technologies and integrating AI-assisted automation within analytics workflows.
- Experience with banking systems or credit union environments is an asset.
- Relevant certifications in data architecture, cloud, analytics, or AI considered an asset.
- Advanced SQL and strong proficiency in data modelling techniques (e.g., star schema, normalized models, semantic modeling).
- Technical proficiency in modern data stack technologies, including ETL/ELT tools.
- Proficiency with analytics and visualization tools such as Power BI or Oracle Analytics.
- Working knowledge with data warehouse platforms such as Lodestar (or similar).
- Strong understanding of database architecture, data pipelines, APIs, and integration patterns.
- Skilled in Python or R for advanced analytics and automation (preferred).
- Familiarity with AI/ML tools, cloud platforms, and modern data architecture paradigms (e.g., lakehouse, event-driven data).
- Understanding of ITIL Framework, considered an asset.
- Strong communication skills with the ability to translate complex data into clear business insight.
- Critical thinker with a hands-on mindset.
- Excellent problem-solving, analytical, and critical-thinking skills.
- Ability to build strong relationships across technical and non-technical teams.
- Curiosity, continuous learning mindset, and a passion for enabling data-driven cultures.