Data Engineer

Pixaera is a company focused on transforming the learning world by integrating gaming and AI into educational experiences. They assist enterprise businesses in transitioning from traditional video to gamified learning experiences.

• Significant professional experience as a Data Engineer, capable of independently owning platforms and customer-facing outputs.
• Proven ability to learn new technologies independently.
• Strong skills in business process analysis and data modeling for reporting.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Excellent written and spoken English.
• Self-motivated and able to thrive in a fully remote work environment.
• Familiarity with agentic coding tools like Claude Code and interest in building AI into data pipelines.
• Proficient in Python and SQL.
• Strong understanding of data structures, algorithms, and system design.
• Experience with data warehousing tools such as Snowflake and data transformation tools like dbt.
• Comfortable creating customer-facing dashboards with BI tools like Omni, Looker, or Metabase.
• Knowledge of software engineering best practices including testing, code review, and CI/CD.
• Experience deploying data solutions to production environments.
• Skills in performance optimization and cost control of data pipelines.
• Experience with public cloud platforms such as AWS, Google Cloud, or Azure.

Nice to have:

• Experience specifically with Omni or migrating between BI tools.
• Backend programming skills in Golang, NodeJS, Postgres.
• Experience setting up prototypes using AWS and Kubernetes.
• Experience working with education or assessment solutions.

• Own customer-facing dashboards and reporting based on the current data model, ensuring accuracy as new content is deployed.
• Manage the full data platform including ingestion (Fivetran), warehouse/data lake (Snowflake), and transformation layer (dbt).
• Transform raw learning and assessment data into actionable insights for customers and internal teams.
• Monitor and maintain reliable, cost-effective data pipelines with appropriate incremental and full-refresh models.
• Develop data products beyond dashboards such as APIs, reports, exports, and accurate content mappings integrated within the publish pipeline.
• Collaborate with backend and frontend engineers to integrate data cleanly into new features and elevate data practices across engineering.