Data Engineer

Industry: Transportation
Company size: 251-10K
Not disclosed

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Job description

A well-established company providing ecological solutions to reduce carbon emission problems with their electric vehicles is looking for a Data Engineer. The engineer will be working extensively with data infrastructure, transformation, designing a data warehouse, and building pipelines. The company has gained a global reach, providing a balanced distribution of shared bikes, scooters, and transit vehicles across continents to reduce the dependence on personal automobiles for short-distance travels. This is an exciting opportunity to work in a highly influential company powering millions of rides globally. This role requires 6+ hours overlap with the PST time zone.


Job Responsibilities:

  • Operate with little supervision and provide solutions for pipeline reliability and data quality
  • Design and implement data models for optimal storage and performant retrieval to meet critical product and business requirements
  • Take responsibility for at least one data content area and build data pipelines for analytical and algorithm needs
  • Ensure high uptime for all data systems (the central data warehouse, data lake, ETL, and real-time processing)
  • Democratize data within the organization by formulating and enforcing best practices across teams
  • Scale up the data infrastructure to meet business needs
  • Work cross-functionally with the product, business, and finance teams 
  • Work actively with Airflow, Python, Fivetran, Kinesis, Git, Tableau, and contribute new ideas
  • Mentor junior members, make architectural decisions and prepare design documents

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years of relevant industry experience as a data engineer
  • Prior experience working with large-scale data warehousing architecture and data modeling
  • Proficiency with cloud-based architecture such as AWS or Google Cloud
  • Core competency with big data technologies such as Snowflake, Redshift, Airflow, Kinesis, Kafka, Spark, and Flink is a plus
  • Track record of leading design reviews and participating actively 
  • Capable of influencing a team’s technical and business strategy by making insightful contributions that impact priorities and approaches
  • Working knowledge of relational databases
  • Expert skills in SQL and high-level languages such as Python, Java, or Scala
  • High-level ability to analyze large data sets to identify gaps and inconsistencies in ETL pipeline 
  • Ability to communicate in English at a high proficiency

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