Note: The job is a remote job and is open to candidates in USA. Pluralsight is a company dedicated to accelerating the technology skills and capabilities of today's tech workforce. The Principal Engineer, Platform Analytics will be responsible for owning the architecture and technical decisions of the Platform Analytics, designing and operating data pipelines, and mentoring junior engineers.
Responsibilities
- Own the architecture of Platform Analytics and the key technical decisions while preserving the consistency guarantee and meeting its latency and freshness targets
- Design, build, and operate the data pipelines and serving layers hands-on: event ingestion and entity/reference ingestion into Snowflake, dbt-governed metric definitions, and a high-performance OLAP serving layer behind a single Analytics API
- Own production performance, reliability, and cost — performance tuning, monitoring and alerting, and resource management — for a customer-facing system
- Curate and model source-system data into trusted, conformed datasets, applying dimensional modeling and engineering best practices
- Build and operate the traditional data-engineering ELT the product depends on to the same standard as the platform-analytics path
- Set the technical bar for the team — code quality, design standards, and ways of working — and mentor senior and mid-level engineers, raising the team's ability to make and hold sound technical decisions
- Partner with the Product Manager and stakeholders to sequence the architecture work ahead of the dependent product roadmap, and communicate technical direction and trade-offs to both technical and non-technical audiences
- Use AI coding tools productively in daily engineering work — accelerating development, testing, and debugging — and help establish effective patterns for their use across the team
Skills
- Requires a minimum of 12 years of related or equivalent experience; or 8+ years and an advanced degree
- Deep, current, hands-on expertise designing and delivering data warehouses and analytical data platforms — including data curation, integration, metadata management, and data-quality processes — with the ability to do this work personally, not only direct it
- Expert SQL development and performance tuning on analytical databases (e.g., Snowflake), with the judgment to hold low-latency, high-concurrency query performance at scale
- Experience with streaming and real-time data processing (e.g., Kafka) and with change-data-capture (CDC) ingestion for entity/reference data
- Experience designing and operating a high-performance OLAP serving layer for customer- or product-facing analytics (e.g., ClickHouse), or strong transferable equivalent
- Experience with dimensional data modeling and with source control, testing, and deployment workflows for ELT (e.g., dbt, git-based CI/CD)
- Experience with workflow orchestration tools (e.g., Apache Airflow) for scheduling, dependency management, and monitoring of production data pipelines
- Demonstrated ability to own architecture and make and hold the key technical decisions on a complex, business-critical system — exercising independent judgment on performance, reliability, scalability, and consistency
- Productive, fluent use of AI coding tools in day-to-day engineering work
- Excellent communication skills — able to align engineers, partner with product and non-technical stakeholders, and mentor more junior engineers
Benefits
- Competitive compensation
- Bonus eligibility
- Comprehensive medical coverage
- Unlimited PTO
- Wellness reimbursement
- Professional development funds
Company Overview
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