Data Analyst

Key Responsibilities 1. Data Product Ownership & Quality Assurance Own analytics-ready datasets and dashboards from requirements through delivery and adoption Lead QA and UAT processes for new datasets, pipelines, and data products Define acceptance criteria, test plans, and validation checks Ensure data accuracy, completeness, usability, and consistency Partner with data engineering to: Investigate root causes of data issues and bugs Prioritize fixes and enhancements Validate deployments before production release Act as a subject-matter expert for data definitions, metrics, and business logic Maintain documentation for data products, schemas, and testing standards 2. Analytics Enablement & Insight Delivery Query and validate complex datasets using SQL and Python Analyze large datasets to identify trends, patterns, and actionable insights Translate analytical findings into clear, business-friendly narratives Support end-to-end analytical deliverables from exploration through operationalization Ensure analytics outputs are trusted, repeatable, and fit for business use 3. Marketing & Experimentation Support Partner with marketing and business teams to: Enable audience segmentation for acquisition, engagement, and retention initiatives Define data needs for targeted and 1:1 campaign execution Support experimentation frameworks by: Defining test/control logic and success metrics Validating campaign data inputs and outputs Ensure campaign data flows are properly tested and production-ready 4. Stakeholder & Cross-Functional Collaboration Act as the primary liaison between business stakeholders and technical teams Elicit, document, and prioritize business requirements for analytics and data products Align privacy, legal, and compliance considerations into data design and testing Collaborate with internal teams and external partners to assess data quality and resolve discrepancies Promote shared understanding of data products and encourage best practices across teams Skills & Competencies Technical Skills Strong proficiency in SQL and working knowledge of Python Experience validating and testing data pipelines, datasets, and dashboards Understanding of data modeling concepts and analytical data structures Familiarity with cloud data platforms and modern data pipelines is a plus Experience working with consumer or customer data preferred Product & QA Skills Experience defining business requirements, acceptance criteria, and success metrics Strong background in QA, UAT, and data validation workflows Ability to balance speed with data quality and governance Comfort operating as a product owner without direct engineering management Soft Skills Excellent communication and data storytelling skills Strong critical thinking and problem-solving capabilities Ability to navigate ambiguity and drive clarity across teams Proven ability to influence stakeholders without formal authority High attention to detail and a proactive ownership mindset Responsibilities Location Full-time remote role Hybrid work option available for select locations (e.g., US or Canada(Toronto) Qualifications Required Qualifications Bachelor's degree in Analytics, Economics, Business Analysis, Marketing, or a related field 3+ years experience working with SQL, Python, or similar analytical tools 1+ year experience in stakeholder-facing roles or product ownership responsibilities Demonstrated experience supporting data-driven decision-making