At a Glance
- Tasks: Lead a dynamic team to design and optimize data pipelines and ML models.
- Company: Join Gore Mutual, a modern mutual insurance company committed to doing good.
- Benefits: Enjoy competitive salary, health benefits, retirement matching, and paid time off.
- Other info: Hybrid work environment with a focus on continuous improvement and innovation.
- Why this job: Make a real impact in transforming the insurance industry with innovative data solutions.
- Qualifications: 5+ years in data engineering or ML Ops, with strong leadership skills.
The predicted salary is between 118500 - 168500 $ per year.
At Gore Mutual, we’ve always set ourselves apart as a modern mutual that does good.
Now, we’re proudly building on that legacy to transform our company—and our industry—for the better.
Effective January 1, 2026, Gore has joined Beneva—the country’s largest mutual insurance company—as part of its Property & Casualty operations in Ontario and Western Canada.
During 2026, Gore will combine its operations with Unica Insurance, Beneva’s Ontario-based subsidiary specializing in niche commercial and personal insurance, creating a stronger, more diversified mutual insurer with greater scale and long-term stability.
Every decision and investment remains anchored in long-term benefits to customers, members, and communities. Come join us.
What will you do?
- Design, build, and maintain that support the ingestion, transformation, and storage of large-scale datasets.
- Optimize data workflows to ensure efficient data processing and availability.
- Develop and implement best practices for deploying, monitoring, and managing robust data pipelines and ML models in production.
- Collaborate with data scientists to ensure seamless integration and deployment of ML solutions.
- Strategy and Planning
- Define the vision, strategy, and roadmap for data engineering and ML Ops in alignment with the company's goals.
- Ensure the scalability, reliability, and efficiency of ML models and data pipelines.
- Team Leadership and Development
- Lead and motivate a high-functioning engineering team, providing coaching to empower members and delivery squads.
- Encourage innovation, experimentation, and best practices within the data engineering team.
- Allocate resources, manage workloads, and set goals to ensure timely, budget-compliant project completion.
- Security and Compliance
- Ensure that data engineering and ML Ops processes adhere to industry standards, regulatory requirements, and security best practices.
- Implement measures to safeguard sensitive data and protect against potential vulnerabilities
- Stay updated on the latest advancements in data engineering and ML Ops technologies and methodologies.
- Implement best practices and drive continuous improvement initiatives to enhance the efficiency and effectiveness of our ML systems.
What will you need to succeed in this role?
- Bachelor’s or master’s degree in computer science, Data Engineering, Software Engineering or a related field.
- Demonstrated experience (5+ years) in data engineering, machine learning operations, or related fields, including a minimum of 2 years in a leadership or managerial role.
- Advanced proficiency in programming languages such as Python, Java, or Scala.
Comprehensive knowledge of data pipeline frameworks (e. g., Databricks) and ML Ops tools (e. g., MLflow, Kubeflow).
- Extensive hands-on experience with cloud platforms (e. g., AWS, Google Cloud, Azure) and containerization/orchestration tools (e. g., Docker, Kubernetes).
- Exceptional problem-solving and analytical skills, with in-depth expertise in data architecture, data modeling, and database systems.
- Strong leadership and team management capabilities, with the ability to motivate and inspire team members. Excellent communication and interpersonal proficiency.
- Ability to excel in a fast-paced and dynamic environment. Proven adaptability and eagerness to adopt new technologies and methodologies.
- High attention to detail and a commitment to delivering high‑quality solutions. Ability to prioritize tasks and manage multiple projects concurrently.
- #LI-Hybrid
The expected base salary range for this position is $118,500 - $168,500.
Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary.
You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.
Please note: This rangereflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels.
During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.
Gore Mutual is proud to offer a comprehensive total rewards package which includes extended health and dental benefits, disability insurance, retirement plan matching, paid time off, recognition and perk programs.
This posting pertains to an existing vacancy that is actively being filled.
Accessibility for applicants
Gore Mutual Insurance Company is committed to providing accommodations for people with disabilities during all phases of the recruiting process, including the application process.
If you require accommodation because of a disability, we will work with you to meet your needs.
Contact us and a human resources representative will consult with you to determine an appropriate accommodation.
Should you request an accommodation during the interview process, please notify your Talent Acquisition Consultant.
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Manager Data Engineering – ML Ops in Toronto employer: Gore Mutual Insurance
Gore Mutual Insurance Company is an exceptional employer that fosters a collaborative and innovative work culture, where your contributions directly impact the company's success. Located in a vibrant community, we offer competitive benefits, professional development opportunities, and a commitment to employee growth, ensuring you thrive both personally and professionally while leading a talented team in shaping our data strategy.
