Analytics Engineer — Sports Data Pipelines & Integrity

DataJobs; New York (NY); Hybrid; USD 130,000 - 150,000; Full time

Benefits offered by this job

Annual bonus

Medical, dental, vision

401(k)

Wellbeing & education support

Job summary

The NBA’s Analytics Engineer role in the Integrity Team focuses on building production-ready datasets by integrating external betting feeds with internal basketball data. You’ll enable anomaly detection, AI-driven capabilities, and ensure data governance under legal scrutiny.

You will own ingestion, OSINT pipelines, and semantic layer maintenance, collaborating with data scientists and full-stack engineers to expose datasets for downstream analytics.

Qualifications

• Bachelor’s degree in a technical or quantitative field.
• Minimum 5 years of experience in analytics engineering or data engineering.
• Experience building analytical data models on cloud platforms.

Responsibilities

• Own ingestion from betting partners and data vendors, normalizing schemas into a conformed model.
• Build and maintain OSINT ingestion pipelines with entity resolution.
• Integrate betting/OSINT data with internal datasets for game context.
• Develop production analytical data models using dbt on Snowflake.
• Create feature-ready datasets for data science and ML workflows.
• Implement automated data quality tests, freshness, and monitoring.

Skills

Advanced SQL

dbt

Snowflake

Dimensional modeling

Sports betting knowledge

Python

Vendor integration

Orchestration & scheduling

Semantic layer

Data quality & monitoring

ML data pipelines

Git workflows

Stakeholder communication

Discretion & handling sensitive data

Independent work

Cross-functional collaboration

Education

Bachelor’s degree in technical/quantitative field

Master’s degree preferred

Tools

dbt

Snowflake

Python

GitHub

Azure DevOps

Databricks

Airflow

Dagster

Prefect

MLflow

Job description

The NBA’s Analytics Engineer role in the Integrity Team focuses on building production-ready datasets by integrating external betting feeds with internal basketball data. You’ll enable anomaly detection, AI-driven capabilities, and ensure data governance under legal scrutiny.

You will own ingestion, OSINT pipelines, and semantic layer maintenance, collaborating with data scientists and full-stack engineers to expose datasets for downstream analytics.