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MetropolisMetropolisNew York, NY

Senior Data Engineer

Designs and owns data architecture, builds/optimizes pipelines and models using Python, SQL, Snowflake, dbt, and AWS. Manages SLAs, data governance, and mentors team; requires 5+ years experience and bachelor's in CS or related.

160k – 220k
On-site5+ YOEData Engineering

About the role

Responsibilities

  • Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
  • Design and own data architecture for large-scale projects while managing operational trade-offs
  • Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
  • Define and manage Service Level Agreements (SLAs) for all owned data sets
  • Implement data security models, ensure privacy compliance, and evolve data governance processes
  • Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
  • Maintain production processes by optimizing complex code using advanced algorithmic concepts
  • Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
  • Mentor team members through actionable feedback to foster collective skill growth
  • Maintain flexibility with availability during evening hours

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field (Master's preferred)
  • 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
  • 5+ years with Python, building scalable Big Data solutions and ETL ecosystems
  • Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
  • Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
  • Familiarity with integration tools like Airflow and Automic, along with working knowledge of CI/CD pipelines
  • Ability to deliver high standards of code quality, system reliability, and performance
  • Deep understanding of modern IaC ecosystem for automated infrastructure deployments
  • Experience with cloud computing services, preferably AWS, including Glue, Airflow (MWAA), DMS, EKS, and SNS

Nice-to-haves

  • Experience with Spark and PySpark
  • Master's degree in Computer Science, Computer Engineering, or relevant field

Compensation

  • Base salary: $160,000 - $220,000 USD annually
  • Total compensation may include healthcare, 401(k), disability coverage, life insurance, stock options, bonuses

Skills

PythonSQLSnowflakedbtAirflowAWSETLELTPostgresMySQLSparkPysparkGlueCI/CDIac

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