Senior Data Engineer

ManulifeToronto, ON
CA$113,000 - CA$163,000Hybrid

About The Position

The Data Engineering Lead is a hands-on technical expert who builds scalable data platforms, data pipelines, automated tools, and reusable data products that expand the organization’s Data & AI capabilities. This role also partners closely with Sales, Marketing, Product, and other business stakeholders to translate opportunities into clear data solutions and to ensure what we build drives measurable business impact and growth.

Requirements

  • Bachelor’s degree (or higher) in computer science or quantitative field (e.g., Mathematics, Physics, Engineering).
  • Advanced experience with databases, data architecture, and modern data engineering practices.
  • Strong programming skills in Python, SQL, Spark.
  • Experience building automated data pipelines, orchestration workflows, and data transformation solutions, ideally in Azure Databricks or similar cloud data platforms.
  • Experience with cloud data technologies—especially Azure, including Azure Databricks—and Data as a Service (DaaS).
  • Demonstrated experience leveraging AI/Generative AI tools (e.g., GitHub Copilot, LLM-based assistants, automation frameworks) to accelerate development, improve code quality, and enhance productivity across the software delivery lifecycle.
  • Ability to collaborate with Sales, Marketing, and other customer-facing stakeholders.
  • Be able to capture business pain points, showcase prototypes and iterate on solutions.
  • Strong communication and storytelling skills; able to simplify complex concepts.
  • Comfortable facilitating sessions, presenting to groups, and engaging partners.
  • Consultative mindset with the ability to link technical work to business outcomes.

Nice To Haves

  • Experience with analytics and visualization tools (e.g. PowerBI) is a plus.
  • Solid understanding of RESTful APIs with FastAPI (authentication, rate limiting, pagination, error handling).
  • Experience in deploying and operating containerized applications on AKS (Azure Kubernetes Service).
  • Good understanding of Agentic AI frameworks like LangChain/AutoGen.
  • Exposure to A2A (Agent to Agent) implementation & Agent scaling.

Responsibilities

  • Design and build scalable data pipelines, automated data tools, and reusable data products on modern cloud platforms such as Azure Databricks to accelerate AI and analytics value delivery.
  • Automate, modernize, and improve data pipelines and engineering processes to increase efficiency, reliability, and scalability.
  • Deliver projects across data ingestion, engineering, visualization, and decision-making.
  • Serve as a data-domain subject matter expert and trusted technical advisor.
  • Build a strong understanding of systems and the data environment by researching, exploring, and testing new data architecture, design ideas, and technologies.
  • Collaborate with internal and external experts to improve data quality, platform reliability, access, and usability.
  • Use technical documentation to develop a holistic understanding of the data domain.
  • Work with data scientists to turn business requests into high-value data products and capabilities.
  • Partner with business teams and data scientists to build, improve, and deliver trusted, analysis-ready data.
  • Help develop conceptual/logical data models, curated data layers, or semantic layers with clear business context.
  • Work with Sales, Marketing, Product, and other teams to understand needs and identify where data and analytics can support growth.
  • Turn business insights into clear technical requirements focused on measurable impact.
  • Explain technical ideas in plain language and confidently present solutions to non-technical audiences.
  • Act as a connector between technical and business teams to keep goals, requirements, and delivery aligned.
  • Help business partners understand and use data and automation effectively.
  • Identify and develop “data champions” to increase profitable use of data.
  • Learn key business concepts from partners and enable creative, effective use of data technologies.

Benefits

  • health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans.
  • various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources.
  • generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence.
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