The Company

Metropolis develops advanced computer vision and machine learning technology that make mobile commerce remarkable. Our platform is already deployed in hundreds of mobility facilities and industries with billions in opportunity. We’re building the digital pipes through which the future of mobile commerce will move.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows.

Position Overview and Responsibilities

At Metropolis, we are building the nextGen end-to-end data ecosystem including Data Ingestion, Data Warehousing, Data Integration, Analytic Data Products and Machine Learning capabilities. We are looking for talented data engineers to help design, build and deploy the data systems. If you are excited about working with Data APIs, Data Vault and Dimensional data modeling, Serverless Cloud platforms, Data Pipeline, Data Lake, ML Ops, etc. you might be interested in this opportunity. In this role, you will help define and build the data tech stack including Snowflake, AWS Redshift, SQL, Python, Scala, SparkSQL, Talend, Airflow, AWS Glue, Tableau, AWS Sagemaker. You will play a key and significant role in enabling the Metropolis business teams to leverage data to meet business goals.

Key Responsibilities

• Collaborate with Application and Engineering teams to build a strong understanding of source data systems and application data models.
• Develop and Implement ETL data pipelines to ingest data from source systems into the Data Lake, Data Warehouse and Data Marts
• Develop and implement ingestion patterns including CDC for batch, event-based, streaming, file base and unstructured data sources.
• Develop and implement data quality and error handling frameworks to ensure data integrity
• Build and maintain relational and dimensional data models
• Evaluate new tools and technologies and assist in architecting the data tech stack
• Perform data analysis for building data solutions for Analytics and ML business use cases
• Develop business data catalog and/or data dictionaries to document data lineages, data definitions and metadata for data domains..
• Optimize and maintain the Analytics tools environment
• Work in agile teams include sprint planning, backlog grooming and program increments.
• Mentor and coach data engineers on the team

Requirements and Qualifications

• Bachelor’s degree in a STEM discipline or related field
• 5-8+ years of relevant hands-on experience in data and analytics domain / teams.
• Expert level proficiency in SQL
• 5+ years experience in data ingestion (batch, streaming, API, etc.) and data integration (ETL) development using Informatica, Talend, AWS Glue or similar.
• 3+ years experience working with cloud data warehouses such as Snowflake, AWS Redshift, Azure, BigQuery or similar.
• 3+ years experience with Data Warehouse architecture including relational and dimensional data models.
• 2+ years experience on Data Visualizations/BI tools including Tableau, PowerBI, Microstrategy, etc.
• 2+ programming experience developing data solutions in Python, Java, Scala or similar
• 2+ years Agile / Scrum experience including participating in daily sprints, backlog grooming and program increments
• Demonstrated ability to adapt to new data technologies and learn quickly
• Ability to communicate across all levels of the organization and work with diverse project teams.