Full-Time

Staff Data Engineer

Posted on 4/2/2024

Metropolis

Metropolis

201-500 employees

Automates parking using computer vision, ML

Data & Analytics
AI & Machine Learning
Real Estate
Consumer Goods

Senior, Expert

Los Angeles, CA, USA

Required Skills
Talend
Microsoft Azure
Agile
Redshift
Python
BigQuery
SQL
Java
AWS
Data Analysis
Snowflake
Requirements
  • 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. Proficiency in Snowflake is strongly preferred.
  • 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.
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 Machine Learning 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.

Metropolis Technologies employs advanced computer vision and machine learning to innovate the parking industry by creating cashless and ticketless solutions. This not only positions the company at the forefront of technological advancement in urban mobility solutions, but also exemplifies a culture of forward-thinking and problem-solving. Working here offers the opportunity to be part of a team dedicated to transforming everyday experiences and leading change in how physical spaces interact with technology.

Company Stage

Series C

Total Funding

$1.9B

Headquarters

Santa Monica, California

Founded

2017

Growth & Insights
Headcount

6 month growth

0%

1 year growth

3%

2 year growth

7%
INACTIVE