Job SummaryWe are seeking a highly technical, execution-focused, and hands-on Data Product Manager to manage the daily lifecycle of our core data assets. In this role, you will treat data as a first-class product, executing the delivery roadmap from initial data ingestion and modeling through to engineering and deployment. You will bridge the gap between complex data infrastructure and operational needs, ensuring our analytical engines, models, and pipelines deliver real-time, automated value directly to the business.
This role requires strong technical execution and product management discipline. You will not focus on front-end user experiences or static dashboards. Instead, you will engineer and optimize the underlying data structures, APIs, and algorithmic logic that power automated decision-making and fuel enterprise workflows within a modern Google Cloud Platform (GCP) ecosystem.
Responsibilities- Own the Data Product Lifecycle: Deliver the roadmaps for assigned data products, tracking development from data sourcing and processing to production implementation and delivery
- Embed Analytics & Intelligence: Connect with business process owners to embed predictive models, rules engines, and data-driven insights directly into operational workflows and daily business applications
- Hands-on Prototyping: Actively build early-stage proof-of-concepts, data mockups, and SQL/Python-based logic prototypes to validate data availability, model logic, and workflow integration prior to full engineering scale
- Translate Data to Action: Transform complex data structures, raw algorithmic outputs, and data tables into clean, actionable, and context-aware guidance streams available at the exact moment decisions are made
- Monitor Product Performance: Track daily data health, product metrics, and pipeline reliability. Continuously monitor performance and refine models to resolve drift, ensure data quality, and maximize business impact
Role Impact
- Operationalize Insights: Maximize data utility and unlock ROI by shifting analytics out of passive, disconnected reporting tools and directly into live business execution
- Systemize Intelligence: Prevent a reliance on intuition or static strategies by systematically injecting proactive, data-driven recommendations into daily operations
- Ensure Decision Consistency: Enable reliable operational scale and higher win rates by standardizing data products and automated logic across diverse segments, regions, and customer footprints
QualificationsCore Data Product Management
- Data Experience: 5+ years of experience working directly with data-centric products, data platforms, data APIs, or analytics infrastructure (e.g., as a Data Product Manager, Technical Product Manager, Data Analyst, or Data Engineer)
- Product Delivery: Experience managing a product backlog, writing technical user stories, participating in sprint cycles, and prioritizing engineering tasks
- Requirement Mapping: Ability to translate defined business goals into structured data requirements, identifying the inputs and logic parameters needed
GCP, BigQuery, & Advanced SQL (Primary Tech Stack)
- Advanced SQL Mastery: Expert-level SQL skills to write highly optimized, complex analytical queries. Proficiency with window functions, Common Table Expressions (CTEs), nested fields, and performance tuning for massive datasets
- Google BigQuery Expertise: Hands-on experience navigating the BigQuery architecture. Competency using BigQuery features like partitioned/clustered tables, materialized views, and BigQuery ML for rapid model deployment
- Google Cloud Platform (GCP) Ecosystem: Solid understanding of core GCP data infrastructure tools (e.g., Cloud Storage, Dataflow, Dataproc, Pub/Sub, Vertex AI) used to orchestrate, store, and stream data across enterprise applications
Technical & Hands-On Prototyping
- Scripting Capabilities: Fundamental proficiency in Python or equivalent scripting languages to manipulate data, connect to cloud APIs, and test functional logic prototypes
- Modern Data Engineering: Practical understanding of basic ETL/ELT pipelines, data transformations (e.g., using dbt within BigQuery), and data warehousing concepts
- API Fundamentals: Good understanding of how APIs and microservices are used to stream data product outputs from cloud environments into target business systems
Analytical & Algorithmic Domain Knowledge
- Predictive & Scoring Logic: Foundational understanding of predictive modeling, scoring algorithms, look-alike logic, and data segmentation frameworks
- Rules Engines: Familiarity with recommendation logic architectures and dynamic optimization rules engines
Collaboration & Communication
- Team Liaison: Ability to communicate clearly and coordinate effectively between technical engineering teams (Data Engineers, Data Scientists) and commercial business users
- Problem Solver: Analytical mindset focused on troubleshooting data flow issues and translating technical complexities into clear project status updates
Stakeholder Management
- Manages stakeholder expectations within and/or across functions
- Identifies and proactively includes correct stakeholders and communications effectively
Qualifications- 5+ years experience preferred
- Bachelor's degree preferred
The targeted pay range for this position in the following location is / locations are:
Canada - Toronto Office TRO : 99,000 - 149,000 CAD / Annual
Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location.
The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience, and relevant education and/or training.
The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.
Equinix BenefitsAs an employee, you become important to Equinix's success. We ensure all your benefits are in line with our core values: competitive, inclusive, sustainable, connected and efficient. We keep them competitive within the current marketplace to ensure we're providing you with the best package possible. So, wherever you are in your career and life, you'll be able to enhance your experience and bring your whole self to work.
Employee Assistance Program: An Employee Assistance program is available to all employees.
Canada Core Benefits: - Insurance: You may enroll in healthcare coverage that is designed to complement the provincial healthcare system, along with life, disability and optional benefit plans that are designed for you and your eligible family members. - Retirement: You may also enroll in Equinix-sponsored retirement or savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP) and Tax-Free Savings Plan (TSFA). - Vacation and Paid Holidays: Equinix offers both vacation and personal time, along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to specific plan or program terms, and to change at Equinix discretion.
