Data Engineer

DATAMAXIS
Dearborn, MI Remote Contractor
POSTED ON 8/13/2024 CLOSED ON 11/10/2024

What are the responsibilities and job description for the Data Engineer position at DATAMAXIS?

Rate: depending on experience

Work location: MI (hybrid)


We are seeking a highly skilled and certified Data Engineer with expertise in Big Data technologies, Kafka, and Google Cloud Platform (GCP). The ideal candidate will have a strong background in designing, building, and maintaining scalable data pipelines, as well as experience with real-time data processing. You will be responsible for ensuring the reliability, efficiency, and scalability of our data infrastructure.

Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines and ETL processes using Big Data technologies.
  • Implement and manage real-time data streaming solutions using Apache Kafka.
  • Architect and manage data storage solutions on Google Cloud Platform (GCP), ensuring high availability and reliability.
  • Collaborate with data scientists, analysts, and other engineering teams to integrate data solutions into various applications.
  • Optimize data systems and pipelines for performance, scalability, and cost-efficiency.
  • Ensure data quality and integrity across all data pipelines.
  • Monitor and troubleshoot data pipelines to ensure continuous and reliable data flow.
  • Document data engineering processes and maintain comprehensive records of all data infrastructure components.
  • Stay up to date with the latest trends and best practices in data engineering, Big Data, Kafka, and GCP.

Qualifications:

Certification: Google Cloud Certified - Professional Data Engineer or equivalent certification.

Experience: 3 years of experience in data engineering with a focus on Big Data technologies.

Technical Skills:

  • Proficiency in Apache Kafka for real-time data streaming.
  • Hands-on experience with Google Cloud Platform (GCP) services such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, etc.
  • Strong knowledge of ETL processes and data pipeline orchestration tools.
  • Experience with distributed data processing frameworks like Apache Hadoop, Apache Spark, etc.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Experience with SQL and NoSQL databases.
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