Principal Analytical Engineer
ShyftLabs
full-time
Posted on:
Location Type: Hybrid
Location: Toronto • 🇨🇦 Canada
Visit company websiteJob Level
Lead
Tech Stack
AWSAzureCloudDistributed SystemsGoogle Cloud PlatformPythonSQL
About the role
- Own the technical vision and architecture for analytics and data platforms, ensuring solutions are scalable, secure, and aligned with enterprise standards.
- Lead the design and implementation of end-to-end data architectures, including data lakes, data warehouses, analytics layers, and ML-ready data pipelines.
- Define and evolve data modelling standards, analytics patterns, and architectural best practices across projects and teams.
- Navigate high levels of ambiguity by decomposing complex business and technical problems, proposing structured solution options, and driving alignment with stakeholders.
- Formulate, compare, and present multiple architectural and technical approaches, guiding clients and internal teams toward optimal long-term solutions.
- Architect and build high-quality, production-grade data pipelines that support analytics, reporting, experimentation, and machine learning use cases at scale.
- Partner directly with clients to understand business objectives, translate them into robust technical designs, and act as a trusted technical advisor.
- Lead and mentor cross-functional teams, including Analytics Engineers, Data Engineers, ML Engineers, and FE/BE developers, setting a high bar for technical quality.
- Influence and contribute to data governance, data quality, observability, and platform reliability initiatives.
- Drive the development of internal data products, reusable frameworks, accelerators, and AI-powered solutions.
- Contribute to technical strategy, roadmap planning, and decision-making across multiple engagements or accounts.
Requirements
- 5+ years of extensive SQL and Python experience, with a strong ability to design, optimize, and troubleshoot complex data systems.
- 5+ years of relevant data engineering or data architecture experience, with the hands-on ability to build and scale enterprise-level data platforms.
- Proven experience designing and implementing data lakes, data warehouses, and modern analytics architectures.
- Demonstrated experience working on AI, ML, or advanced analytics initiatives, including preparing data for modeling and production use.
- Strong foundation in data modeling, distributed systems, and performance optimization.
- Experience working with major cloud platforms (AWS, GCP, or Azure) in production, enterprise environments.
- Proven ability to operate independently with full ownership, while influencing technical direction across teams and stakeholders.
- Track record of successfully navigating ambiguity and driving outcomes in complex, client-facing environments.
- Experience leading, mentoring, and influencing senior engineers and cross-functional teams.
- Prior experience in a data, analytics, or ML-focused organization or large-scale enterprise project.
Benefits
- Comprehensive Benefits: We cover 100% of health, dental, and vision insurance premiums for you and your dependents which means no out-of-pocket costs. Eligibility starts from day one itself.
- Growth & Learning: Access extensive learning and development resources to keep leveling up your skills.
- Hybrid Flexibility: Enjoy a hybrid model with three days per week in our Toronto office.
- Downtown Toronto Office: Work in the heart of the city.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
SQLPythondata architecturedata engineeringdata lakesdata warehousesdata modelingmachine learningperformance optimizationdistributed systems
Soft skills
leadershipmentoringproblem-solvingcommunicationinfluencingnavigating ambiguitycollaborationtechnical advisorystakeholder alignmentindependence