Analytics and Operations Manager

Posted Yesterday
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Toronto, ON
Mid level
Software
The Role
As an Analytics and Operations Manager, you will analyze and interpret complex datasets using SQL, develop data models, support decision-making with actionable insights, and collaborate across teams to enhance operational efficacy and drive strategy implementation.
Summary Generated by Built In

About the Job & Shakudo


At Shakudo, we are building the world’s first operating system for data and AI. We use the term operating system in the truest sense of the word. Like iOS, Windows and Linux, Shakudo’s end-to-end OS offers ever-evolving, automatically operated, best-of-breed open-source components tailored to each business's unique needs.



As an Analytics and Operations Manager at Shakudo, you will be integral to our operations team, leveraging data to drive informed decision-making and operational success. Your primary focus will be on gathering, analyzing, and interpreting complex datasets to uncover insights and create actionable recommendations. You will collaborate with internal teams, present data-driven findings to stakeholders, and support the development and implementation of strategies. The ideal candidate is a detail-oriented, analytical thinker who thrives in a dynamic environment and enjoys solving complex problems. Your ability to adapt, work cross-functionally, and contribute to a data-first culture will be critical to our success.

What You'll Do

  • Analyze and interpret large datasets using SQL to support data-driven decision-making and uncover insights. Experience with Hubspot and Python would be a plus.
  • Develop and implement scalable data models and analytics workflows, providing actionable insights to optimize company strategies.
  • Analyze operational and financial data to identify trends, improve performance, and optimize company strategies.
  • Communicate complex ideas and collaborate with stakeholders across business operations and other departments to gather requirements and deliver actionable recommendations.
  • Support the design and implementation of scalable systems and processes for internal reporting and performance tracking.
  • Monitor key performance indicators (KPIs) and deliver insights to guide strategic decision-making.
  • Identify opportunities for automation and process improvement within business operations using data-driven approaches.
  • Prioritize and execute core and ad-hoc projects in support of strategic initiatives and to enable sound, data-driven business decisions.
  • Jump into any area of the business that requires resourcing and problem solving.

Requirements

  • Experience with VS Code is required.
  • Advanced SQL Skills (e.g., Database Structure, Staging Tables, and ETL, Common Table Expressions (CTEs), Subqueries, Advanced Joins, Query Optimization, Dynamic SQL).
  • Experience with Hubspot and Python and other analytics tools is also a strong advantage.
  • Bachelor’s degree in Mathematics, Statistics, Engineering, Business, or a related field.
  • 4+ years of experience in data analytics or a similar role.
  • Strong analytical, problem-solving, and communication skills with the ability to work effectively in diverse teams.
  • Bias for action and ownership mentality.
  • Comfort with ambiguity and operating in a fast-paced environment.
  • Ability to work full-time from our Toronto office.

Shakudo is an equal opportunity employer and encourages candidates of all backgrounds to apply. We foster diversity and inclusivity and welcome applications from a broad range of backgrounds and experiences.

Top Skills

Python
SQL
The Company
Toronto, Ontario
29 Employees
On-site Workplace
Year Founded: 2021

What We Do

Shakudo is an easy to use data platform that has everything that a data team needs to deliver products end-to-end and continuously adds new integrations that data teams want. By using Shakudo data teams become less reliant on engineers. Shakudo’s platform automates many common engineering and development tasks, and comes with built-in tools that simplify the process of scaling data solutions

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