Demo

Senior Data Engineer

EV.Careers
CA Full Time
POSTED ON 2/8/2025
AVAILABLE BEFORE 5/7/2025

This is a remote position.

EV.Careers is currently seeking a fulltime Senior Data Engineer for one of our partners that is revolutionizing electric vehicle charging infrastructure across the globe. In this position you will architect and develop scalable data solutions that power critical business decisions and help accelerate the adoption of sustainable transportation. As a key member of the data engineering team youll work with cuttingedge AWS technologies to build and optimize data pipelines that drive innovation in the EV charging space.

Responsibilities :

  • Design and implement robust data pipelines using AWS services including Kinesis Glue and Lambda for both batch and streaming processing
  • Architect and maintain scalable data lake and warehouse solutions utilizing AWS S3 and Redshift
  • Develop and optimize ETL / ELT workflows for diverse data types while ensuring data quality and governance
  • Partner with analytics and machine learning teams to deliver efficient data solutions for advanced reporting needs
  • Create near realtime data processing systems using Apache Spark on EMR
  • Implement automated monitoring and validation processes to maintain data integrity
  • Integrate and optimize thirdparty tools for visualization and analytics
  • Lead troubleshooting efforts for complex data infrastructure challenges
  • Create comprehensive documentation for data architecture and processes

Requirements

7 years of experience in data engineering or related field

Extensive AWS expertise particularly with S3 Redshift Glue Lambda Kinesis and Athena

Strong background in data lake and warehouse architecture

Advanced SQL skills and experience with both relational and NoSQL databases

Proven experience with ETL / ELT tools including Apache Airflow dbt or AWS Glue

Experience in integrating and optimizing BI tools like Domo for advanced reporting

Demonstrated proficiency with message bus technologies (Kafka SQS SNS)

Strong Python or Scala programming skills

Experience with InfrastructureasCode tools like Terraform or CloudFormation

Knowledge of data security best practices and compliance requirements

Preferred Qualifications :

  • 10 years of data engineering experience
  • Experience with data mesh architectures
  • AWS Certified Data Analytics Specialty certification
  • Bachelors degree in Computer Science Data Engineering or related field
  • Expertise in CI / CD practices and tools
  • Background in eventdriven architectures
  • Experience with generative AI applications in data workflows
  • Value monitoring logging and auditing to track the health and performance of data systems.
  • Strong troubleshooting and debugging skills
  • Excellent communication skills
  • Proven ability to implement scalable solutions with clear SLOs and SLAs.
  • Knowledge of renewable energy or EV industry
  • Benefits

    Paid time off (vacation and flex time)

    Health insurance

    Life insurance

    Dental insurance

    401k with company matching

    Monthly EV stipend

    Yearly ongoing education stipend

    and more!

    7 years of experience in data engineering or related field Extensive AWS expertise, particularly with S3, Redshift, Glue, Lambda, Kinesis, and Athena Strong background in data lake and warehouse architecture Advanced SQL skills and experience with both relational and NoSQL databases Proven experience with ETL / ELT tools including Apache Airflow, dbt, or AWS Glue Experience in integrating and optimizing BI tools like Domo for advanced reporting Demonstrated proficiency with message bus technologies (Kafka, SQS, SNS) Strong Python or Scala programming skills Experience with Infrastructure-as-Code tools like Terraform or CloudFormation Knowledge of data security best practices and compliance requirements Preferred Qualifications : 10 years of data engineering experience Experience with data mesh architectures AWS Certified Data Analytics Specialty certification Bachelor\'s degree in Computer Science, Data Engineering, or related field Expertise in CI / CD practices and tools Background in event-driven architectures Experience with generative AI applications in data workflows Value monitoring, logging, and auditing to track the health and performance of data systems. Strong troubleshooting and debugging skills Excellent communication skills Proven ability to implement scalable solutions with clear SLOs and SLAs. Knowledge of renewable energy or EV industry

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