Otter.ai-posted 1 day ago
$185,000 - $230,000/Yr
Full-time • Mid Level
Mountain View, CA
101-250 employees

We are looking for a Senior Data Engineer to join our Data Platform team and build the core data foundations that power analytics, experimentation, and decision-making across the company. In this role, you will design and own foundational data models, pipelines, and platforms that enable self-serve analytics and trustworthy insights at scale. You will partner closely with Growth, Product, Sales, Marketing, Data Insights, and Engineering teams as a technical thought leader who helps teams extract meaningful value from data. This is a high-ownership role in a growing company, and you will have a direct impact on how data is collected, modeled, and used to drive the business forward.

  • Build and own foundational data models that enable self-serve analytics and key business metrics
  • Design, operate, and scale reliable data pipelines and platforms
  • Partner with stakeholders to translate business needs into trusted data products
  • Influence data collection and logging standards across production systems
  • Establish best practices for data modeling, quality, and governance
  • Implement data quality checks, statistical validation, and anomaly detection
  • Provide technical leadership that improves data reliability and data literacy
  • 5+ years of experience in data engineering
  • Has a Bachelor's degree in Computer Science or equivalent experience
  • Has strong programming skills in Python and SQL
  • Has expertise with cloud data warehouses such as Snowflake, BigQuery, or Databricks
  • Has experience building and maintaining ETL/ELT pipelines
  • Is experienced with workflow orchestration (e.g., Airflow, dbt)
  • Has strong data modeling skills and understands how to design for analytical workloads
  • Has experience with cloud platforms (preferably AWS)
  • Has worked in fast-paced tech, AI or SaaS environments
  • Experience with data governance, data catalogs, and data quality frameworks
  • Familiarity with BI or data visualization tools
  • Experience with experimentation or A/B testing frameworks
  • Exposure to ML pipelines, feature engineering, or applied data science
  • Experience with streaming or near-real-time data systems
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