Job Description
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
Job Tags
Remote job, Full time