Senior Analytics Engineer

ZBD is a licensed global payment service provider building embedded financial infrastructure for games and interactive entertainment.

Series C0 current maintainers0 active leads
Hoboken, United States
About ZBD

ZBD provides game-native payment infrastructure for money entering, moving through, and leaving games. Its current offering includes Embedded Accounts, Embedded Payouts, Embedded Rewards, Branded Debit Cards, Bitcoin and Lightning payments, developer APIs, and the ZBD consumer app. Services are operated through ZEBEDEE, LLC in the United States and ZEBEDEE EUROPE B.V. in the EEA.

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Skills

About the Role

You will own and build the transformation layer as dbt is introduced on a new data warehouse. You will design trustworthy dimensional models, tests, and documentation; translate ambiguous business questions into durable data models; and establish scalable patterns for analytics and reporting. You will partner with finance, compliance, and product stakeholders to define requirements and data definitions, monitor data assets, resolve or escalate issues, and contribute to ingestion, orchestration, warehouse configuration, analysis, and decision support when needed.

Requirements

  • 7+ years of combined experience in analytics engineering, data engineering, or analytics with substantial modeling ownership
  • Strong analytical SQL skills, including complex joins, window functions, and performance-aware queries
  • Fluency in data modeling and dimensional modeling
  • Experience with a transformation framework; dbt preferred, with Dataform, SQLMesh, or equivalent accepted
  • Experience with a cloud data warehouse such as Redshift, Snowflake, BigQuery, or Databricks
  • Familiarity with an orchestration engine such as Airflow, Dagster, or Prefect
  • Familiarity with BI and visualization tools such as Metabase, Hex, Looker, or Tableau
  • Knowledge of Git, CI/CD, testing, and documentation
  • Ability to gather requirements with finance and compliance stakeholders

Responsibilities

  • Own the transformation layer, including dimensional models, tests, and documentation
  • Translate business questions and ambiguous requirements into durable data models
  • Establish scalable patterns for advanced analytics and reporting
  • Partner with finance, compliance, and product to define requirements and data definitions
  • Monitor data assets and resolve or escalate issues before stakeholders are affected
  • Contribute to data ingestion, orchestration, warehouse configuration, analysis, and decision support when needed

Hiring Process

Applied → Meet-and-Greet → Technical Interview → Final Interview