Staff Data Engineer



Software Engineering, Data Science
Seattle, WA, USA
Posted on Tuesday, July 18, 2023

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 next-gen end-to-end data ecosystem including Data Ingestion, Data Warehousing, Data Integration, Analytic Data Products and Machine Learning capabilities. We are looking for a hands-on thought leader to drive the technical vision, design and development of 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, Databricks, Python, Scala, SQL, 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 the source data systems
  • Leverage your understanding of the source data systems to design and build conceptual, logical and physical data models for the Data Warehouse, Data Marts and MDM repositories.
  • Collaborate with the analytics and business teams to architect and implement performant data solutions for Analytics and ML business use cases.
  • Design and lead the implementation of frameworks and best practices for data ingestion, data integration and ETL processes.
  • Design and lead the implementation of data quality framework including data quality metrics and continuous data quality monitoring, assessment and resolution.
  • Create business data catalog and/or data dictionaries to document data lineages, data definitions and metadata for data domains.
  • Assist with establishing best practices and standards for data privacy and data security.
  • Work closely with data engineering, analytics, business and offshore/onshore consulting teams to ensure alignment on architecture and design.
  • Provide technical oversight and mentor development teams
  • Hands-on development to support DW and ETL initiatives.

Requirements and Qualifications

  • Bachelor’s degree in a STEM discipline or related field
  • 10+ years of relevant hands-on experience in data and analytics domain / teams.
  • Expert level proficiency in SQL
  • 5+ years of demonstrated experience in building relational and dimensional data warehouse data models. Experience with Data Vault methodology would be a plus.
  • 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.
  • 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.
  • Preferred local to Santa Monica, CA, Seattle, WA, or New York City, NY. Hybrid working environment (3 days in office per week). Other locations considered on a case-by-case basis.