Maverick Games is a fast-growing Ontario-licensed iGaming operator offering an online casino and sportsbook experience. We operate in a dynamic, data-rich environment where rapid insights power decisions across marketing, product, operations, and finance. You'll join a lean team where your work will have real impact.
Role Overview
We're looking for a Data Analyst who will become our go-to person for deriving business intelligence across multiple domains: player activity, marketing funnels, payments/withdrawals, player retention & churn, and regulatory reporting. You'll build dashboards, manage data pipelines, partner with cross-functional teams (marketing, product, finance, compliance) and help shape our data-driven culture.
Key Responsibilities
Take end-to-end ownership of reports from data ingestion and transformation, through validation and reconciliation, to final delivery and ongoing maintenance.
Design, build, and maintain production-grade data pipelines and ETL/ELT workflows using Python, ingesting data from the gaming platforms, CRM systems, external service providers, and analytics tools.
Automate reporting workflows using Python, schedulers, and APIs, minimizing manual effort and reducing operational risk.
Develop and own analytics-ready data models and reporting datasets (facts, dimensions, aggregates) that serve as the single source of truth for business and regulatory reporting.
Ensure data quality, reliability, and observability by implementing validation checks, reconciliations, monitoring, and alerting across pipelines and reports.
Build and maintain recurring operational, financial, and regulatory reports covering key iGaming metrics (GGR, NGR, deposits/withdrawals, ARPU, churn, retention, promotional ROI).
Own regulatory and compliance reporting pipelines for Ontario (iGO) and other jurisdictions, ensuring traceability, reproducibility, audit readiness, and clear data lineage.
Partner closely with Marketing, Product, Operations, and Finance to translate reporting requirements into scalable data models and automated pipelines.
Perform deeper analytical work where required, including player segmentation, cohort and lifecycle analysis, funnel analysis, and payment/withdrawal behaviour.
Identify gaps in tracking, instrumentation, and data availability, and propose improvements to data architecture, schemas, and ingestion strategies.
Document data pipelines, transformations, reporting logic, and business definitions to ensure long-term maintainability and stakeholder trust.
Act as a technical owner for analytics engineering standards, reviewing work and mentoring others where appropriate.
Requirements
Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, or a related field (or equivalent practical experience).
4+ years of experience in data analytics, analytics engineering, or data engineering roles, with demonstrated ownership of production data pipelines.
Strong proficiency in Python, including building and maintaining ETL/ELT jobs, data transformations, and automation scripts.
Advanced SQL skills and experience designing queries and data models for performance, correctness, and reusability.
Solid understanding of data modelling principles, data quality frameworks, and analytics engineering best practices.
Familiarity with version control (Git) and CI/CD practices for data pipelines and analytics code.
Ability to translate business questions into scalable data solutions and clearly communicate insights to both technical and non-technical stakeholders.
Comfortable operating in a fast-paced environment with evolving requirements and multiple stakeholders.
Nice-to-Have
Prior experience in iGaming, sportsbook, fintech, or payments-heavy environments.
Marketing analytics experience (UTM tracking, attribution modelling, conversion funnels).
Experience with compliance and regulatory reporting in highly regulated industries.
Additional Details
Contractor role, 40 hours per week.
Permanent ongoing engagement, we're looking for someone who can grow with us.
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