Full-Time Tech Lead Data

We are looking for a Tech Lead, Data to join our Data Team!

This is a mid-level Subject-Matter-Expert position leveraging a significant technical background to guide the Data Team's technical strategy in accordance with the department's culture of iterative, autonomous development and deployment.

With a keen focus on security and scalability concerns, you will work closely with our Product Managers, Data Team Lead, and Staff Developers to design and implement systems and processes enabling Zensurance to effectively harness data in growing the business.

As an individual contributor and subject-matter-expert, you will coach and mentor peers or professional-level developers, and assist the Engineering Leadership Team with employee training and development to continuously enhance the team's technical capabilities and delivery excellence.

This is a remote-first role within the GTA.

Responsibilities:

• Collaborate with project stakeholders and the Data team to design, build, and implement scalable, user-friendly data products using Snowflake, dbt, and Looker.
• Lead the Data team in planning for and accommodating large migrations in upstream source systems.
• Collaborate with Product Management to examine, adjust, and break down roadmap items into epics, and break down epics into discreet, actionable, appropriately sized tickets in the team's backlog.
• Oversee the planning and deployment of advanced data products (machine learning models, LLM powered applications).
• Provide a technical perspective on organizational objectives within the team's scope of activities. Analyze requirements, identify areas of concern, and provide recommendations based on extensive technical background.
• Using POC models, design and implement systems and infrastructure in accordance with the team's vision and culture.
• Adhere to the organization's security strategy using a security-first mindset.
• Discuss various strategies and architecture, and highlight trade-offs for potential solutions.
• Perform code reviews, ensure pull requests accurately reflect the acceptance criteria of the tickets they address.
• Use quality metrics to identify gaps in testing strategy. Work with teams to recommend solutions that are in accordance with accepted testing frameworks.
• Define and prioritize areas of technical debt and bugs, take into consideration outcomes of the incident management process, and address them with the team.
• Foster a culture of iterative deployability with awareness of cycle time and failure rates.
• Coach and mentor the Data team, work to expand their technical knowledge and skills.
• Use a systematic approach to debugging to diagnose issues within the application.
• Write unit tests as well as higher-level tests to ensure application quality and stability.
• Consistently produce production-ready code that is easily testable, easily understandable, and accounts for edge cases and errors, using comments and other documentation strategies where appropriate.
• Follow Agile practices, suggest improvements, and participate in team events.
• Develop a strong understanding of the company's goals and initiatives, help the engineering team deliver on those goals/initiatives.
• Ensure technical standards like accessibility, performance, security, maintainability, functional correctness, operability and observability are observed in the modules developed and maintained by the team.
• Document decisions, research and guides to foster and build a culture of continuous learning and continuous improvement.
• Perform other duties as assigned.

Requirements:

• University degree or college diploma in a recognized technical, vocational or academic program (preferably in Engineering or Computer Science) or equivalent work experience.
• 7+ years building and supporting user-facing data applications.
• 5+ years building and maintaining data pipelines and ETL systems with Python.
• 5+ years data modeling with SQL.
• 3+ years developing and deploying machine learning models.
• 3+ years orchestration experience with Kubernetes, Airflow.
• 2+ years designing scalable and distributed systems.
• 2+ years using Infrastructure as Code tools such as Terraform.
• 2+ years experience and experimentation with LLMs (prompt engineering, fine tuning).
• 2+ years of experience coaching and mentoring data analysts, data engineers, and data scientists.
• Experience implementing secure data practices to adhere to compliance standards.
• Extensive experience with the Scrum framework and Agile methodologies.
• Familiarity with goal setting frameworks such as OKRs.
• Experience with MongoDB, dbt, Snowflake, Segment, and Looker.

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