Data Engineer Lead

About the Opportunity Randstad is partnering with a major Financial Services/Insurance organization that values Care, Commitment, Community, and Confidence. This organization is transforming its data landscape, building a next-generation Snowflake data platform to support growing data needs and enable AI and GenAI capabilities. We are seeking a collaborative and resourceful Data Engineer Lead to join the IT Data Engineering Delivery team and help drive this core modernization initiative. The role reports into the AVP of Data Engineering and requires applying deep knowledge across modern and legacy data platforms to architect, design, and implement scalable data ecosystems. Key Note: If you feel you are a match to the qualifications and experience listed for this position please do feel free to send your up to date CV directly to SHERYL.SAN.LORENZO@RANDSTADDIGITAL.COM. Due to the highly specialized nature of this role, only candidates who meet the following mandatory technical requirements will be contacted: 8 years of professional experience in data delivery (at least 5 high-impact data projects from inception through warranty) 3 years of hands-on experience with Snowflake, dbt Core/Cloud, and AWS Cloud Technologies. 5 years of experience coding in multiple languages, including Python and Java. Deep knowledge of NoSQL databases (e.g., MongoDB). Please ensure your resume clearly reflects these skills and experience levels. The Role: What You'll Do As a Lead, you will define the technical roadmap and drive the architecture, design, and implementation for robust, scalable data pipelines. This is a critical leadership role that requires a strong blend of hands-on engineering, solution design, and team mentorship. Key Responsibilities: Solution & Architecture Leadership: Lead the architecture, design, and analysis of data solutions, ensuring alignment with business goals and standards. Data Strategy & Standards: Define and drive data engineering standards and best practices across the organization. Data Pipeline Development: Lead the design and implementation of high-performance data pipelines using tools like dbt Core/Cloud. Code Ownership: Write and maintain clean, reusable, and optimized code using SQL, Python, Shell, and Terraform. Data Governance & Quality: Champion data quality and governance, including designing data models (conceptual, logical, physical) and creating robust test plans. Mentorship & Team Elevation: Guide and mentor Data Engineers and project team members, fostering engineering excellence. What You'll Bring: Core Expertise We are looking for a dedicated, inquisitive, and adaptable leader with a strong technical foundation and the drive to deliver high-impact results. Essential Experience & Skills: Professional Experience: 8 years of professional experience, delivering over 5 high-impact data projects from inception through warranty. Modern Data Stack: 3 years of hands-on experience with Snowflake, dbt Core/Cloud, and AWS Cloud Technologies. Coding Expertise: 5 years experience with coding in multiple languages, including expert proficiency in Python and experience with Java. Database Depth: Deep knowledge of relational databases (Snowflake, PostgreSQL, Amazon Aurora), big data platforms (Hadoop), and NoSQL databases (MongoDB). Pipeline & Orchestration: Hands-on experience with orchestration tools like Zena and/or AWS Managed Airflow. Technical Skills: Expert-level proficiency in SQL, Python, Shell, and Terraform, with a focus on performance and reusability. Bonus Skills: Familiarity with the Insurance industry processes/systems, and exposure to operationalizing AI/ML & GenAI models are a plus. Location/Model: Hybrid model, requiring 3 days per week onsite. A minimum of 1 day per week must be spent in the Markham, ON office. Culture: Focus on corporate wellness and employee-driven programs centered on diversity and inclusion.

Location: Greater Toronto Area, Canada, CA

Posted Date: 11/4/2025