Senior Analytics Engineer

Posted 16ds ago

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Job Description

Senior Analytics Engineer managing Mood's AI-enabled data architecture and analytical insights. Collaborating with various teams to enhance analytics infrastructure and decision-making capabilities.

Responsibilities:

  • Design and maintain scalable data models that support reporting, experimentation, and machine learning
  • Own the semantic layer and ensure consistent metric definitions across dashboards, analyses, and data products
  • Develop and maintain transformation pipelines that turn raw data into clean, trusted analytics datasets
  • Partner with analytics and business teams to translate analytical needs into well-structured data models
  • Ensure the analytics layer is designed to support AI, experimentation frameworks, and predictive modeling
  • Build and maintain reliable data pipelines using modern transformation frameworks
  • Improve data freshness, performance, and scalability across the analytics stack
  • Implement testing, monitoring, and validation frameworks to ensure data quality and reliability
  • Work closely with data engineering to optimize warehouse performance and pipeline efficiency
  • Support ingestion and modeling of new data sources across product, marketing, CX, and operations
  • Power the dashboards and reporting used across marketing, product, operations, and leadership
  • Optimize the BI layer to improve performance, usability, and trust in analytics outputs
  • Reduce manual reporting by building reusable datasets and scalable reporting infrastructure
  • Partner with analysts to ensure analytics workflows are efficient and well-supported by the data layer
  • Design data models that support experimentation frameworks, predictive models, and AI applications
  • Collaborate with data science to operationalize model outputs into reporting and decision workflows
  • Ensure clean, well-documented datasets that enable faster development of machine learning and AI-driven products
  • Maintain clear documentation for data models, metrics, and transformation logic
  • Define and enforce standards for data quality, metric definitions, and modeling best practices
  • Ensure stakeholders can easily understand and trust the data powering business decisions
  • Contribute to a culture of data ownership, transparency, and high-quality analytics.

Requirements:

  • 4–7+ years of experience in analytics engineering, data engineering, or business intelligence
  • Strong SQL skills and experience building scalable transformation pipelines
  • Hands-on experience with modern analytics engineering tools (dbt or similar highly preferred)
  • Experience working with cloud data warehouses (BigQuery strongly preferred)
  • Experience designing data models that power BI tools such as Looker, Looker Studio, Tableau, or similar
  • Strong understanding of dimensional modeling, semantic layers, and analytics data architecture
  • Experience building reliable data pipelines and implementing data testing/validation frameworks
  • Comfort working closely with analysts, engineers, and business stakeholders
  • Experience supporting experimentation, growth analytics, or product analytics is a strong plus
  • Familiarity with data structures required for machine learning or AI-driven analytics is a plus
  • Strong documentation habits and a commitment to building trusted analytics infrastructure.

Benefits:

  • Remote work options
  • Professional development opportunities