Blueprint helps organizations unlock value from existing assets by leveraging cutting-edge technology to create additional revenue streams and new lines of business. As an Analytics Engineer, you will serve as a bridge between raw data and decision-making. You will transform large volumes of complex gameplay and event-streaming data into scalable, reliable, and business-ready data products.
Requirements
- Python — 2+ years
- SQL — 2+ years
- Data Modeling — 2+ years
- 1+ years working as an Analytics Engineer or Data Engineer with consistent business collaboration on large-scale systems.
- Experience building and maintaining enterprise-scale data pipelines—especially logs and event-stream data—on cloud platforms using tools such as Spark and Airflow (Azure preferred).
- Strong Python proficiency with a “pythonic” development approach; solid SQL skills.
- Familiarity with DevOps and DataOps practices.
Responsibilities
- Design scalable data models, architect dataflows, and develop abstractions to support analytics and ML workloads that evolve with business needs.
- Use modern data engineering best practices to build and maintain automated, object-oriented data pipelines that produce clean, enriched, and reliable datasets.
- Advance the data infrastructure by developing reusable components, frameworks, and capabilities that improve quality, velocity, and consistency.
- Identify and analyze multi-structured data or metadata from numerous sources to determine the most accurate and effective inputs for analytics.
- Build deep subject-matter expertise across business and data domains to support data consumers and stakeholders with access, interpretation, and insights.
- Partnering closely with data consumers, engineering teams, and product stakeholders, you will design data models, build automated pipelines, and develop frameworks that enable analytics, machine learning, and deeper understanding of player behavior.
- Collaborate extensively with users and stakeholders: ~60% coding (70% data transformations, 30% infrastructure)
Other
- Strong critical-thinking skills and a creative, open mindset toward problem solving.
- Proven experience designing and optimizing analytic solutions and data products that drive measurable business outcomes.
- Strong data analysis and exploration skills for identifying, preparing, and validating data and metadata.
- Business acumen and the ability to translate ambiguous needs into practical analytics engineering solutions.
- Video game industry or player experience—understanding gameplay systems, player behavior, or game telemetry is a meaningful plus.
