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Data Platform Engineer @ Betwarrior

Not specifiedOnsiteFull-time
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About this role

JOIN OUR TEAM

BetWarrior is a next-generation digital gaming company with a bold mission: to redefine the way people experience sports betting and casino entertainment across Latin America.

With a dynamic and diverse team, deep market insights, and cutting-edge technology, we're creating an experience that is personalized, responsible, and always player-first.

Great people, bold ideas, and a sharp focus on user experience set us apart

Purpose

We're looking for a Data Platform Engineer to shape and scale BetWarrior's data ecosystem as a strategic capability. This is a high-ownership, high-impact role: you'll define how we build, scale, and evolve our data platform — and you'll drive the data foundations that power our product, analytics, and AI roadmap.

You'll work cross-functionally with Engineering, Product, BI, Data Science, Finance, Marketing, and Leadership. If you combine deep technical depth with strategic thinking and want to join a fast-growing environment with a clear track to expand your scope and long-term strategic impact — this is your move.

In this role, you’ll

• Design and own scalable data platforms for real-time and batch processing across Azure, AWS, and Snowflake.

• Architect warehouse solutions, semantic layers, and data-sharing capabilities across domains.

• Set the standards for data modeling, orchestration, lineage, observability, and quality.

• Build the AI/ML data infrastructure: feature stores, training pipelines, vector databases, RAG architectures, and LLM-ready data products.

• Evaluate and integrate AI-native tooling into the data platform.

• Build and optimize robust ELT/ETL pipelines — low-latency, trusted, business-critical.

• Lead technical decisions on orchestration, CI/CD, and infrastructure automation.

• Leverage AI-assisted development practices (code generation, automated testing, AI code review) to raise velocity and standards.

• Build self-healing, self-optimizing pipelines using ML-driven observability.

• Own monitoring, alerting, and operational excellence for the data platform.

• Ensure compliance with governance, security, masking, and regulatory standards.

• Collaborate closely with data leadership today to co-create BetWarrior's data platform strategy, with the mindset to own and drive its long-term evolution.

• Influence technical and operational decisions, acting as a strategic partner to the business as the data domain scales.

• Mentor and pair with engineers and analysts, raising engineering standards across the team.

• Drive experimentation, personalization, fraud prevention, and player analytics capabilities.

• Champion data culture and democratize data access across the company.

What we look for in an exceptional candidate

• 7+ years in Data Engineering, Data Platform, or Analytics Engineering.

• Snowflake expertise: performance optimization, architecture, governance, advanced platform capabilities.

• Solid experience with Azure and AWS for large-scale data processing.

• Expert-level SQL and strong Python skills.

• Deep understanding of modern data architecture: dimensional modeling, semantic layers, distributed systems.

• Experience with DataOps, CI/CD pipelines, infrastructure automation, and orchestration frameworks.

• Experience building data infrastructure for AI/ML workloads (feature stores, vector DBs, or LLM integration).

• Familiarity with AI-assisted engineering practices and tools.

• Strong cross-functional stakeholder management and organizational communication skills.

• Proven ability to mentor, elevate technical teams, and guide architectural vision.

• You've been the go-to person for data architecture decisions in at least one previous org.

• Excellent English communication skills. Fluency in Spanish is a valuable plus.

Bonus points if you also have

• Experience in gaming, betting, fintech, or other high-volume transactional environments.

• Hands-on experience with KNIME Analytics Platform.

• Experience with semantic layer technologies (e.g., AtScale, dbt Semantic Layer).

• Experience implementing AI-driven data quality, anomaly detection, or automated pipeline optimization.

• Background in building self-service analytics ecosystems or experimentation frameworks.

We expect every team member to live our values

Accountability & Ownership – Take charge, own your craft

Reliability – Deliver with quality and consistency

Teamwork – Collaborate, challenge, and grow together

Winner Spirit – Compete with purpose and grit

Wellbeing – Build a career that energizes you

Curiosity & Innovation – Keep questioning. Keep improving

Skills

Product & Tech

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