Lead Data Analyst
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Job Description
Lead Data Analyst for Maverick Games, an Ontario-licensed iGaming operator. Responsible for data analytics, automation, and regulatory reporting in a remote role.
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 SQL, ingesting data from the gaming platforms, CRM systems, external service providers, and analytics tools.
- Automate reporting workflows using SQL, 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 SQL, including building and maintaining ETL/ELT jobs, data transformations, and automation scripts, as well as 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.
- Proficiency in Google Sheet/Excel for any additional analysis.
Benefits:
- Health insurance
- Professional development opportunities
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