Analytics Engineer, Integrity (Sports Betting)

Location: New York, USA; hybrid work with remote work available one day per week

Salary: $130,000–$150,000 per year

Company

hirify.global is a global sports and media organization operating professional basketball leagues, digital products, and international basketball programming.

What you will do

• Own ingestion and normalization of betting partner, operator, vendor, OSINT, and other semi-structured data feeds.
• Integrate betting and investigative data with schedules, play-by-play, box scores, tracking, officiating, and player availability data.
• Develop production-ready dbt models on Snowflake using layered staging and mart designs, dimensional modeling, and incremental processing.
• Build curated datasets and pipelines for data science, machine learning, anomaly detection, backtesting, and production inference.
• Implement orchestration, automated data quality checks, freshness and volume monitoring, reconciliation, alerting, and dependency management.
• Collaborate with data scientists, engineers, basketball experts, Legal, attorneys, and investigators while documenting lineage, definitions, assumptions, and access controls.

Requirements

• Advanced SQL and production experience developing complex analytical data models.
• Production experience with dbt, Snowflake, data warehousing, dimensional modeling, testing, documentation, and performance optimization.
• Proficiency in Python for ingestion, API integration, and data processing.
• Experience integrating messy, high-volume, semi-structured, and unstructured data from multiple vendors and operating orchestrated pipelines.
• Understanding of sports betting markets and basketball data, including odds, line movement, player props, play-by-play, box scores, and tracking data.
• Bachelor’s degree in a technical or quantitative field and at least five years of experience in analytics engineering, data engineering, or analytical data modeling.

Nice to have

• Experience with Databricks, Spark, Delta Lake, Unity Catalog, MLflow, or comparable orchestration platforms.
• Experience with entity resolution, identity matching, record linkage, MLOps, integrity, surveillance, fraud, AML, trust and safety, sports, gaming, or regulated environments.

Culture & Benefits

• Collaborative work across data science, engineering, basketball, Legal, and investigative functions.
• Confidential, time-sensitive work requiring strong discretion, auditability, and legally defensible data practices.
• Medical, dental, vision, life, disability, fertility and family-forming assistance, wellbeing, and mental health benefits.
• Educational assistance, HSA and dependent care FSA options, 401(k), vacation, sick time, and personal days.
• Eligibility for an annual discretionary performance bonus.