Remote Analytics Engineer for Integrity & Data Pipelines

Sports Careers; New York (NY); Hybrid; USD 120,000 - 160,000; Full time

Job summary

NBA in New York seeks an Analytics Engineer to own ingestion and transformation of data powering the Integrity Team’s gaming policy initiatives. You will consolidate feeds from betting partners, OSINT, and vendors into a unified model and integrate with internal basketball data for in-game context.

You will develop production analytics models in dbt on Snowflake, ensure data quality, and collaborate with data scientists and lawyers on investigations.

Qualifications

• Advanced SQL skills with demonstrated experience developing complex analytical data models.
• Production experience with analytics engineering frameworks such as dbt, including testing, documentation, macros, and managing a large model DAG.
• Production experience with Snowflake, including performance and cost management such as warehouse sizing, clustering, and query tuning.
• Strong understanding of dimensional modeling, data warehousing, and analytics engineering best practices.
• Understanding of sports betting markets - odds, line movement, limits, player props, and market maker behavior - and basketball data such as play-by-play, box score, and tracking data.
• Proficiency in Python for ingestion, API integration, and data processing.
• Experience integrating data from multiple external partners or vendors, including messy, high-volume, semi-structured, and unstructured sources.
• Experience building and operating orchestrated data pipelines.

Responsibilities

• Own the ingestion of data from disparate betting partners, operators, and data vendors and normalize them into a conformed model of markets, wagers, prices, and accounts.
• Build and maintain ingestion pipelines for OSINT and other unstructured or semi-structured sources, including entity resolution.
• Integrate betting and OSINT data with internal league basketball data to analyze activity in game context.
• Develop production-ready analytical data models in dbt on Snowflake with dimensional modeling, layered staging and mart designs.
• Create reusable pipelines and feature-ready datasets to support data science and machine learning work.
• Implement automated data quality testing, freshness and volume monitoring, and reconciliation checks on incoming feeds.
• Build and manage orchestration and scheduling for pipelines with dependency management and alerting.
• Develop a semantic layer with standardized definitions and metrics for consistency across teams.
• Document models, sources, lineage, and assumptions for auditability.
• Onboard new betting partners and adapt to vendor schema changes without breaking downstream consumers.
• Collaborate with data scientists and full-stack engineers to expose datasets to platforms and UI.
• Apply access controls and retention practices to sensitive betting and investigative data.

Skills

Advanced SQL

dbt

Snowflake

Dimensional modeling

Data warehousing

Python

API integration

Data pipelines

Collaboration

Vendor integration

Tools

dbt

Snowflake

Job description

NBA in New York seeks an Analytics Engineer to own ingestion and transformation of data powering the Integrity Team’s gaming policy initiatives. You will consolidate feeds from betting partners, OSINT, and vendors into a unified model and integrate with internal basketball data for in-game context.

You will develop production analytics models in dbt on Snowflake, ensure data quality, and collaborate with data scientists and lawyers on investigations.