Senior/Principal Analytics Engineer at Bellota Labs

Redwood City, California, United States -

Full Time

Start Date

Immediate

Expiry Date

04 Jun, 26

Salary

250000.0

Posted On

06 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ETL Pipelines, Data Modeling, Databricks, SQL, Python, Data Quality, Third-Party Integrations, Regulatory Compliance, Financial Reconciliation, Production Monitoring, Data Architecture, Cross-functional Collaboration, PII Handling, Security, Communication Skills, Tableau

Industry

Computer Games

Description

At Bellota Labs, we are a fast-paced, hypergrowth startup poised to revolutionize the gaming world with ClubWPT Gold, a groundbreaking product from the World Poker Tour. Driven by innovation, game integrity, and exceptional customer experiences, we are on a mission to set new standards in online gaming. We are now looking for a Senior/Principal Analytics Engineer to join our dynamic team. This key role will own the end-to-end data and analytics infrastructure that powers business decisions across Finance, Marketing, Product, and Operations. Join us and be part of something big as we redefine the gaming landscape! \n Key Responsibilities: Design, build, and maintain production ETL pipelines and data models on Databricks, supporting daily and hourly business-critical workflows. Own the analytics data layer from raw ingestion through dimensional modeling to BI tool-ready outputs while ensuring data quality, freshness, and reliability. Build and maintain integrations with third-party platforms, including mobile attribution, CRM, payment processors, and ad platforms. Develop and maintain regulatory compliance data systems. Partner directly with Finance, Marketing, Product, and CustOps stakeholders to translate business questions into data solutions from ad-hoc analyses to automated reporting. Build financial reconciliation pipelines with 99%+ accuracy to support revenue tracking, cost allocation, and executive reporting. Monitor production job health, triage failures, and maintain SLAs across 20+ scheduled pipelines. Drive data architecture decisions, establish conventions, and document systems for long-term maintainability. Experience: 5+ years of experience in data engineering, analytics engineering, or a hybrid data role, delivering production-grade pipelines and business-facing analytics. Advanced SQL skills, including window functions, MERGE patterns, incremental loads, and complex multi-table joins. Strong Python proficiency for ETL workflows, API integrations, and data transformations. Experience owning a full data stack as the primary data professional in a fast-moving environment. Proven ability to work cross-functionally, translating requests from non-technical stakeholders into reliable data products. Demonstrated experience handling PII, financial data, and compliance-sensitive workflows with a focus on security and accuracy. Exceptional communication skills, with the ability to explain data findings clearly to stakeholders. Preferred Technologies (Nice to Have): Hands-on experience with Databricks (Unity Catalog, Delta Lake, Dashboards, Genie) Tableau (datasource creation, extract management, dashboard development) REST API integration experience (marketing platforms, CRM systems, payment providers) Familiarity with BigQuery or cross-cloud data workflows Claude Code expertise with an understanding of its capabilities and limitations Experience with statistical modeling or marketing analytics Git/GitHub-based analytics development workflow Experience in gaming, fintech, or regulated industries \n $200,000 - $250,000 a year \n Lead High-Impact Projects – Play a key role in delivering innovative gaming experiences to a global audience Collaborate Across Borders – Work with talented teams across Asia and the US Fast-Paced Growth – Be part of a hypergrowth startup with ambitious goals Competitive Benefits – Enjoy a top-tier compensation package

Responsibilities

This role involves designing, building, and maintaining production ETL pipelines and data models on Databricks to support critical business workflows across Finance, Marketing, Product, and Operations. Key duties include owning the analytics data layer, building integrations with third-party platforms, and developing financial reconciliation pipelines with high accuracy.