Location : Preference to have candidates based in Toronto, next best, candidates would be located in Vancouver. Hybrid work environment of 1 - 2 days onsite. On behalf of our client, Affinity is seeking a Principal Engineer, Data Solutions who will hold a senior technical leadership position, responsible for ensuring the quality, scalability, and effectiveness of data and analytics solutions within Enterprise Data & Analytics function. This role serves as the technical right-hand. You will set standards, mentor team members, evaluate complex solutions, and deliver hands‑on technical work for the organization's most challenging data problems. Individual contributor role Key Responsibilities Technical Leadership & Standards (40%) Set the Technical Bar : Define and enforce standards for data modeling, analytics engineering, and BI development across all Data Solutions squads Solution Evaluation : Review and validate technical designs for major initiatives, ensuring architectural soundness and alignment with enterprise patterns Vendor Management : Evaluate proposals from consulting partners and technology vendors; hold vendors accountable for quality and delivery Quality Assurance : Conduct code reviews, model reviews, and technical assessments to maintain high standards in alignment with governance best practices Hands‑On Technical Delivery (35%) Build Reference Implementations : Create exemplary data models, dbt projects, and BI dashboards that serve as templates for the organization Solve Complex Problems : Tackle technical challenges beyond current team capabilities, from advanced SQL optimization to complex dimensional modeling Develop Data Models : Design and implement scalable, well‑documented data models using dbt, Snowflake/Fabric, and modern analytics engineering practices Hands‑On Coding : Write production SQL, Python, and data transformation logic daily (60%+ hands‑on work) Upskill Data Analysts/Product Managers : Teach effective due diligence, solution design, and technical requirement translation Mentor Analytics Engineers :



Provide structured guidance on data modeling patterns, dbt best practices, and analytical thinking Conduct Training : Lead technical workshops, lunch‑and‑learns, and documentation initiatives Foster Technical Culture : Build a culture of engineering excellence, continuous learning, and quality‑first thinking Qualifications 6-8+ years in analytics engineering, data engineering, business intelligence, or related technical roles Vendor/partner management experience evaluating and holding consulting firms or technology vendors accountable Mentorship experience upleveling junior and mid‑level data professionals Core Technical Expertise Expert‑level SQL (complex queries, optimization, window functions, CTEs) Data modeling and dimensional design (star schema, snowflake, data vault) dbt (data build tool) or equivalent transformation frameworks Modern cloud data warehouses (Fabric, Databricks) Power BI or Tableau (DAX, calculated fields, performance optimization) Python for data analysis and automation Apache Airflow or similar orchestration tools Git/version control and CI/CD practices Data quality, testing, and observability frameworks Data governance and security best practices Technical Judgment : Can evaluate solutions and articulate trade‑offs clearly; knows when to be pragmatic vs. principled Teaching Ability : Can explain complex technical concepts to non‑technical audiences and mentor others effectively Hands‑On Mindset : Prefers writing code to drawing diagrams; leads by example Intellectual Curiosity : Stays current with up-to-date data practices; eager to learn and experiment Ownership Mentality :



Takes pride in quality; doesn't ship "good enough" when excellence is achievable Enterprise Data Architecture & Delivery Excellence 7+ years of experience designing, building, and operationalizing enterprise‑scale data platforms within large, complex organizations (ideally $1B+ in annual revenue). Proven ability to translate business strategy into scalable data architectures that support analytics, reporting, and advanced use cases across multiple stakeholder groups. Advanced Data Modeling & Semantic Design Expertise 7+ years of experience with modern data modeling approaches, including dimensional modeling, Data Vault, and metrics/semantic layers. Strong understanding of how to design models that balance performance, scalability, governance, and ease of consumption for downstream analytics, BI, and data science teams. Modern Data Stack Implementation Experience 7+ years of production experience working with leading cloud data platforms and tools such as dbt, Snowflake, Databricks, or Microsoft Fabric (Preference given to candidates with direct Fabric and Azure ecosystem experience). Highly proficient in SQL and Python, with a proven track record of building reliable, testable, and maintainable data pipelines in production environments. Stakeholder Management & Business Partnership Strong stakeholder management skills with the ability to translate complex business requirements into practical, scalable technical solutions. Proven experience partnering with business leaders, product owners, and engineering teams, while confidently challenging assumptions, managing expectations, and pushing back when requirements conflict with architectural standards, timelines, or long‑term platform sustainability. Salary range: $120K - $150K Affinity is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All employment is decided on the basis of qualifications, merit and business need. #J-18808-Ljbffr

📌 Affinity Principal Engineer Data Solutions (Toronto)
🏢 Affinity
📍 Toronto