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Metropolis

Senior Analytics Engineer

Designs and builds large-scale data warehouses and transformation pipelines using Snowflake, dbt, SQL, and Python. Partners cross-functionally to deliver actionable insights, mentors on best practices, and ensures data quality and performance. Requires 5+ years experience.

130k – 175kNew York, NYData EngineeringOnsite5+ YOE
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About the role

Responsibilities

  • Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
  • Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
  • Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
  • Manage and optimize DAGs, including troubleshooting task failures and improving run times
  • Implement metadata management, data lineage, and security principles such as least-privilege access
  • Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
  • Partner with engineering, data science, and business stakeholders to own project scopes
  • Mentor others on data best practices to drive impact through your data vision
  • Provide architectural guidance to ensure data is accessible and actionable across the company
  • Drive technical excellence within the data engineering and analytics domain

Requirements

  • 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
  • 3+ years of experience with dbt
  • Owned large-scale data projects that drove significant impact through effective cross-functional partnering
  • Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
  • Expert at SQL, window functions, and query optimization for complex data manipulations
  • Applied performance best practices, including partitions, sort keys, and incremental modeling
  • Designed systems using test-driven approaches to ensure data quality and flow integrity
  • Familiarity with ELT processes and tools to prepare and clean data for analysis
  • Skill in using tools like dbt to build data transformation pipelines
  • Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices

Nice-to-Haves

  • A dbt certification

Compensation

  • Base salary: $130,000 - $175,000 USD annually

Skills

SnowflakeSQLdbtPythonData VaultStar SchemaDagsELTData LineageWindow Functions

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