Tech Lead – Data

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 sources 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+ building and maintaining data pipelines and ETL systems with Python.
• 5+ years data modelling 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.