Senior Data Engineer Lead

Position Overview This is a critical leadership and hands-on role within our Information Technology Enterprise Data Services Group, focused on accelerating company's multi-year journey to build a next-generation data platform on Snowflake to enable advanced AI and GenAI capabilities. You will serve as a Staff Engineer-level technical leader, responsible for the architecture, design, and implementation of robust, scalable enterprise data solutions. Key Requirements & Core Technical Skills (Must-Haves) Snowflake (Database/Data Warehouse): Deep expertise in modern cloud data warehousing architecture and performance. dbt (Core/Cloud) (Data Transformation): Expert-level proficiency in modeling and transforming data within Snowflake. Python (Programming Language): Core skill for data pipeline development, scripting, and dbt integrations. AWS (Cloud Computing): Practical experience with relevant AWS services (e.g., EC2, S3, Airflow). What You’ll Do Technical Leadership & Strategy Define and Drive Strategy: Shape the technical roadmap, data engineering strategy, and best practices for the Enterprise Data Services group. Solution Architecture: Lead the development of both high-level (working with Enterprise Architecture) and low-level solution designs for enterprise-scale data ecosystems, ensuring alignment with business goals. Mentorship & Excellence: Provide technical guidance, code review, and mentorship to Data Engineers and project teams, fostering a culture of engineering excellence and delivery focus. Pipeline Development: Lead the design and implementation of highly scalable, high-performance data pipelines, primarily utilizing dbt for transformation and AWS Managed Airflow/Zena for orchestration. Advanced Coding: Write and maintain clean, reusable, and high-quality code in SQL, Python, Shell, and Terraform, with a focus on performance and maintainability. Data Modeling: Design and review conceptual, logical, and physical data models to support new and evolving business requirements. Quality & Governance: Champion data quality, governance, and cataloging practices across the platform. Agile Leadership: Lead agile ceremonies, ensure a delivery-focused mindset, and drive the timely execution of data initiatives. Cross-Functional Collaboration: Work closely with Architects, Data Designers, QA Engineers, and Business stakeholders to deliver cohesive, customer-centric data products. Issue Resolution: Perform root cause analysis and implement effective solutions for complex, high-priority data issues. What You’ll Bring Extensive Experience: Proven track record of architecting and delivering complex, high-impact data projects from inception to production. Core Technical Stack: Mandatory expertise in Snowflake, dbt, Python, and AWS. Advanced Expertise: Deep knowledge of relational databases (e.g., PostgreSQL, Aurora) and modern coding practices in SQL and Python. Resilience & Communication: Exceptional communication and presentation skills (technical and business), with the ability to thrive in fast-paced, high-pressure environments. Domain Knowledge (Asset): Familiarity with insurance industry processes and systems. AI/ML Exposure (Asset): Experience in operationalizing AI/ML and GenAI models. Certifications (Asset): Having two or more certifications such as SnowPRO Advanced Data Engineer, dbt Developer, or AWS Cloud Practitioner is a strong advantage, though a willingness to attain them within 3-6 months is required. Seniority Level Mid-Senior level Employment Type Full-time Job Function Information Technology Industries IT Services and IT Consulting, Software Development, and IT System Custom Software Development Referrals increase your chances of interviewing at Randstad Digital by 2x Get notified about new Data Engineer jobs in Markham, Ontario, Canada. #J-18808-Ljbffr