Data Engineer

Aristocrat

. Compose, build, and maintain scalable data pipelines extracting data from casino source systems, transforming it, and loading optimized datasets for analytics and downstream applications .

Posted 11/2/2026full-timeAustin • Texas • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining scalable data pipelines using Python and Node.js, with a strong focus on data integrity, quality, and performance optimization. Proficient in data modeling and ETL orchestration, capable of collaborating effectively with cross-functional teams to deliver analytical solutions.

Highest-signal resume keywords

Data Pipeline DevelopmentPython ProgrammingNode.js ProgrammingETL OrchestrationSQL Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ModelingETL/ELT PatternsQuery OptimizationData ValidationData Quality AssurancePerformance TuningTransactional Data ProcessingGraph DatabasesLinux Environments

Soft Skills

Attention to DetailTechnical CommunicationIndependent Problem Solving

Tools & Technologies

ETL ToolsData Processing FrameworksData Analytics Platforms

Industry Keywords

Casino Data SystemsAnalytics Use CasesProduction WorkflowsData Integrity

Tech Stack

Tools & technologies

ETLJavaScriptLinuxNeo4jNode.jsPythonSQL

About the role

Key responsibilities & impact

Compose, build, and maintain scalable data pipelines extracting data from casino source systems, transforming it, and loading optimized datasets for analytics and downstream applications
Write efficient, production-quality Python and Node.js code meeting reliability, performance, and maintainability criteria
Develop and maintain data models representing business domains and supporting analytical use cases
Use ETL orchestration tools to schedule, monitor, and manage production workflows
Optimize queries and data processing logic for large volumes of transactional data
Ensure data integrity through validation, testing, and observability practices
Investigate and resolve data quality issues, pipeline failures, and performance bottlenecks
Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver solutions
Document pipelines, data models, and technical decisions

Requirements

What you’ll need

4+ years of professional experience in data engineering or a closely related field
Strong SQL skills
Hands-on experience with data modeling for analytics or reporting use cases
Proficiency in Python and Node.js for data processing and pipeline development
Experience with ETL orchestration platforms to develop, schedule, and manage production data workflows
Solid understanding of ETL/ELT patterns and trade-offs in crafting data pipelines at scale
Familiarity with Linux environments for pipeline deployment and operational tasks
Ability to work independently on well-defined problems and make sound technical decisions without close supervision
Strong attention to detail and dedication to data quality and reliability
Ability to explain technical decisions and data concepts to non-technical collaborators
Experience with graph databases such as Neo4j is a plus but not required

Benefits

Comp & perks

Annual bonuses and incentives may be available depending on role and location
Health and wellbeing benefits may be available depending on role and location
Paid time off may be available depending on role and location
Retirement plans may be available depending on role and location
Insurance coverage may be available depending on role and location
Other local or statutory benefits may be available depending on role and location