Job Description:
The Senior Engineer, Platform Analytics builds and operates the data pipelines and models behind Platform Analytics - the customer-facing analytics experience that delivers a single, trustworthy source of truth for the metrics customers use to measure learning progress. This is a deeply hands-on role focused on traditional data-engineering ELT - ingesting, curating, and modeling data into trusted, conformed datasets - while contributing to the target-state platform-analytics architecture. They partner closely with the engineers in the data org and use AI coding tools fluently to build faster and better.
Who you're committed to being:
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You enjoy learning and are open to new ways of doing things.
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You are not afraid to be yourself, experiment, make mistakes and learn from them, ask questions, or voice your concerns.
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When communicating you are self-aware, insightful, and proactive.
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You are a team member first and individual contributor second. You are aware that high-performing teams are only as strong as their weakest link.
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You believe in continuous improvement and request frequent feedback from others.
What you'll do:
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Build and operate the data pipelines that feed Platform Analytics - event ingestion and entity/reference ingestion into Snowflake - to a high standard of reliability and quality.
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Build and operate the traditional data-engineering ELT to create a reliable source of truth in the data warehouse.
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Contribute to the data models, curating and modeling source-system data into trusted, conformed datasets and applying dimensional modeling and engineering best practices.
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Support production performance, reliability, and cost - performance tuning, monitoring and alerting, and resource management.
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Help evolve the platform toward its target-state architecture, implementing the design and providing architectural and scale recommendations.
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Lead the development lifecycle for your work - implementation, testing, and deployment - collaborating with the team to deliver and maintain the platform.
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Help mentor junior engineers and contribute to team standards for code quality and ways of working.
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Use AI coding tools productively in daily engineering work - accelerating development, testing, and debugging.
Experience you'll bring:
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Familiarity with high-performance OLAP serving layers (e.g., ClickHouse) for product- or customer-facing analytics.
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Experience reducing reliance on integration/middleware tooling by migrating transformation logic into governed models.
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Experience partnering with a data governance function on company-wide standards, schema/version control, and PII classification.
Requirements:
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Requires a minimum of 8 years of related or equivalent experience; or 6+ years with an advanced degree.
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Strong, current, hands-on experience designing and delivering data warehouses and analytical datasets - including data curation, integration, and data-quality processes.
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Strong SQL development and performance tuning on analytical databases (e.g., Snowflake).
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Experience with streaming and real-time data processing (e.g., Kafka) and with change-data-capture (CDC) ingestion for entity/reference data.
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Experience with dimensional data modeling and with source control, testing, and deployment workflows for ELT (e.g., dbt, git-based CI/CD).
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Experience with workflow orchestration tools (e.g., Apache Airflow) for scheduling, dependency management, and monitoring of production data pipelines.
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Productive, fluent use of AI coding tools in day-to-day engineering work.
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Ability to provide architectural, scale, and reliability recommendations, and to collaborate effectively within an Agile team.
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Good communication skills - a strong collaborator and trusted teammate, able to partner with... For full info follo application link.