Role Description

Turn 10 Studios is seeking a Data Engineer to join the Data Pipeline team and help design, build, and support modern data platforms that power studio‑wide decision making. This role focuses on developing scalable, high‑quality data pipelines and analytics systems using Azure‑based technologies. The Data Engineer will partner closely with business, design, test, and development teams to shape how data is captured, modeled, and consumed, enabling test‑driven methodologies and a culture of data‑driven development.

• Design, build, and maintain scalable ETL and ELT pipelines supporting real‑time and batch analytics workloads.
• Develop and optimize data models within lakehouse and warehouse architectures to support analytics and reporting needs.
• Implement data processing solutions using Databricks, Azure Data Factory, Azure Synapse Analytics, and related services.
• Ensure data quality, reliability, and performance across ingestion, transformation, and consumption layers.
• Partner with cross‑functional stakeholders to define data requirements and improve how data is captured and used.
• Create and maintain clear, concise technical documentation for data pipelines, models, and processes.
• Establish documentation and knowledge‑sharing practices that improve discoverability and reuse across teams and studios.
• Advocate for modern engineering practices and contribute to the evolution of the studio’s data architecture.

Performance will be measured based on:

• Quality, reliability, and scalability of delivered data solutions
• Adherence to project timelines and delivery commitments
• Effectiveness of documentation and knowledge sharing
• Collaboration with stakeholders and contribution to data‑driven decision making

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical discipline, or equivalent professional experience.
• Demonstrated expertise in SQL for analytics and data engineering use cases.
• Proven experience designing and implementing scalable ETL processes, including data movement, orchestration, and quality controls.
• Hands‑on experience with modern big data analytics platforms, including data lakes, distributed processing frameworks, and columnar storage formats.
• Experience building and operating cloud‑hosted data systems, with strong preference for Microsoft Azure.

Requirements

• Azure Data Factory, Databricks, Azure Synapse Analytics
• Spark‑based data processing
• Data lake and lakehouse architectures
• Parquet and Delta Lake formats
• Azure Data Explorer and Kusto Query Language
• Data modeling for analytics and reporting
• Data quality, governance, and observability practices

Benefits

• Opportunity to work on the front edge of modern data engineering using Databricks, Azure Synapse Analytics, and Azure Data Explorer.
• Direct impact on studio‑wide decision making, test‑driven development, and data‑driven culture.
• Exposure to large‑scale lakehouse and warehouse analytics systems handling both real‑time and batch data.
• Collaborative environment where data engineering directly influences business, design, testing, and development outcomes.

Assessment Process

Candidates will be evaluated through a combination of technical interviews, practical problem‑solving discussions, and assessment of prior experience building and supporting modern data platforms. Emphasis will be placed on applied data engineering skills, architectural judgment, and documentation practices.