Senior Data Engineer

The Company 

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time. 

The Role 

As a Senior Data Engineer at Metropolis, you will play a key role in shaping both customer-facing and business-facing data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impacts thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond. 

Responsibilities 

• Collaborate with engineers, product managers, and data scientists to understand data needs, and develop end-to-end data pipelines, solutions, and foundational data sets. 

• Design and own the data architecture for large-scale projects, making informed decisions about design and operational trade-offs. 

• Build, launch, and optimize sophisticated data pipelines, data models, and visualizations that support diverse use cases across multiple products or domains. 

• Define and manage Service Level Agreements (SLAs) for all data sets within areas of ownership. 

• Implement data security models based on privacy requirements, ensure compliance with safeguards, address data quality issues, and evolve data governance processes. 

• Solve complex data integration challenges using optimal ETL/ELT patterns, frameworks, and query techniques for both structured and unstructured data sources. 

• Maintain and enhance existing production processes by optimizing complex code using advanced algorithmic concepts. 

• Optimize pipelines, dashboards, frameworks, and systems to streamline data artifact development. 

• Mentor team members, providing and receiving actionable feedback to foster skill growth and collaboration. 

• Ensure flexibility with availability during evening hours. 

Requirements and Qualifications: 

• Bachelor's degree in computer science, Computer Engineering, or a relevant technical field; a master's degree is 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. 

• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt as a plus. 

• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems. 

• Hands-on experience with RDBMS such as MySQL, MS SQL Server, and Postgres. 

• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines. 
• Ability to deliver high standards of code quality, system reliability, and performance. 
• Experience with Spark and PySpark to handle large-scale data processing and enhance data pipeline efficiency.