Data Engineer

• Practice Data

• Technologies Business Intelligence Jobs and Data Recruitment

• Location United States, United States

• Salary NON 160,000

• Type Permanent

I am partnered with a company who have built a technology platform that provides the end to end orchestration of data, systems and applications to manage connected spaces as an integrated technology platform.

They are looking for a Data Platform Engineer to join their Data Platform Team. This is a hands-on builder role focused on owning the delivery of production data pipelines for sports and entertainment venues. You will build and maintain the pipelines that ingest ticketing data, point-of-sale transactions, venue events, and fan engagement signals into their unified platform, processing millions of records across major arenas in the United States and internationally.

You will work within architectural patterns established by their Senior Data Engineers, but you own the build end-to-end: implementation, testing, deployment, and ongoing reliability. Your code will run on game days in some of the biggest venues in the world. If you want to ship to production every week and watch your pipelines light up when 20,000 fans walk through the gates, this is the role.

Responsibilities

• Build, deploy, and maintain production data pipelines using Azure Data Factory and Synapse Analytics following established architectural patterns
• Ingest high-volume data from venue event streams, ticketing platforms, and POS systems using Azure Event Hubs and Stream Analytics
• Write and optimize data transformations in PySpark and Spark SQL within Azure Databricks to process millions of records per hour
• Implement and manage data storage across Azure Data Lake Gen2, Synapse, and SQL Server based on existing data models
• Deploy Azure data services using Terraform within established infrastructure patterns
• Build automated validation and unit testing to ensure pipeline reliability and data quality across multi-tenant environments
• Own pipeline monitoring, troubleshoot failures, and resolve data issues to meet SLA commitments
• Collaborate with Senior Data Engineers to turn technical designs into performant, production-ready code

Requirements

• 3-5 years building and deploying production data pipelines in a cloud environment
• Strong Python skills, specifically PySpark and pandas, for building reusable transformation modules
• Solid SQL skills with a focus on writing efficient queries against large datasets
• Production experience with a major cloud data stack (Azure preferred; equivalent AWS or GCP experience is fine since patterns transfer)
• Familiarity with CI/CD practices and pushing code through automated pipelines (GitHub Actions, Azure DevOps, or similar)
• Track record of owning pipeline reliability, not just initial builds but ongoing monitoring and incident response
• Builder mindset: you care about code quality, performance, and shipping on schedule
• Experience with ticketing, point-of-sale, or venue management data systems
• Knowledge of sports and entertainment industry data
• Experience with real-time analytics and dashboard development (Power BI, Tableau)

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