Data Engineer

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At Triton, we're where passion meets purpose. Our values — Passion, Integrity, and Mastery — are more than words; they drive everything we do. We're relentless in our pursuit of excellence, always innovating and pushing boundaries to create extraordinary events. Join our world class team, and you'll work in a dynamic, collaborative environment that encourages you to think big and grow. You'll be surrounded by like-minded professionals, where your ideas are heard, and your hard work is recognized. We believe in rewarding dedication with competitive compensation and real opportunities for advancement. Are you ready to make an impact

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JOB PURPOSE

The Data Engineer (Databricks) is a key role responsible for designing, building, and maintaining Triton's modern data platform. This position focuses on transforming raw data from multiple sources into reliable, well-structured datasets that power analytics, reporting, and strategic decision-making across the organization.

This role requires a product-oriented and business-aware engineer who can bridge the gap between technical systems and business needs. The Data Engineer will work closely with AI, product, operations, and marketing teams to ensure data is accessible, trustworthy, and actionable.

KEY RESPONSIBILITY

• Design, build, and maintain scalable data pipelines using Databricks (Spark/PySpark, Delta Lake).
• Develop and manage batch and near real-time data ingestion from internal systems, SaaS tools, and APIs.
• Implement and maintain lakehouse architecture following medallion principles (Bronze, Silver, Gold layers).
• Create and optimize data models for analytics, including dimensional models for reporting and dashboards.
• Serve clean, curated datasets to BI tools (Power BI, Tableau, Looker) and support analysts and data scientists.
• Ensure data quality through validation checks, monitoring, and pipeline testing.
• Collaborate with business teams to translate key metrics, funnels, and requirements into production-ready datasets.
• Contribute to data governance practices including cataloging, access control, and documentation (Unity Catalog).
• Optimize performance and cost efficiency of data workflows within Databricks.
• Support CI/CD practices and version control for data pipelines.

JOB REQUIREMENTS:

• 2–3 years of experience in Data Engineering or similar role.
• Strong hands-on experience with Databricks ecosystem (Spark, PySpark, Delta Lake, SQL).
• Experience building end-to-end data pipelines (ingestion, transformation, serving).
• Solid understanding of data modeling concepts (dimensional modeling, lakehouse architecture).
• Familiarity with REST APIs and integrating data from multiple sources.
• Experience with BI tools such as Power BI, Tableau, or Looker.
• Knowledge of Git workflows and basic CI/CD practices.
• Strong problem-solving skills and attention to detail.
• Ability to work cross-functionally and translate business needs into data solutions.
• Good communication skills in English.