Data Engineer
PlayStation Global23 days ago
Responsibilities
- Build scalable pipelines that ingest, transform, and combine infrastructure, engineering, financial, and product data.
- Develop cost and allocation models connecting infrastructure consumption to workloads, services, features, and products.
- Partner with engineering teams to identify infrastructure telemetry and instrumentation requirements.
- Analyze infrastructure cost, utilization, capacity, and unit economics to support business decisions.
- Create trusted metrics, datasets, dashboards, and analytical tools for engineering, product, Finance, and leadership.
- Establish practices for data quality, testing, observability, documentation, and reproducibility.
- Explore new data sources and technologies for understanding and operating infrastructure.
Requirements
- At least 3 years of experience in a similar role focused on production data pipelines, data models, and analytical systems.
- Advanced SQL skills and proficiency with Python or a similar data-oriented programming language.
- Experience with modern data platforms and tooling such as Snowflake, Databricks, dbt, and automated ETL/ELT pipelines.
- Strong analytical skills and the ability to investigate data, challenge results, and communicate clear conclusions.
- Experience working with large, complex datasets across multiple systems and levels of granularity.
- Ability to translate ambiguous business and technical problems into measurable requirements and scalable data solutions.
- Experience with current analytics and visualization tools.
- Familiarity with teams and engineering systems using on-premises and cloud infrastructure.
- Strong communication and cross-functional collaboration skills.
- Bachelor’s degree in computer science preferred.
- Preferred experience with AWS, Google Cloud, or Azure billing and usage data; Kubernetes telemetry, networking, or data center operational data; infrastructure cost allocation, unit economics, capacity planning, forecasting, or FinOps; and connecting infrastructure consumption to product or business metrics.
Tech Stack
Categories
Data Engineering