Data Engineer

4 Months ago • 5-8 Years • Data Analyst • DevOps

Job Summary

Job Description

This is a remote, full-time Data Engineer position requiring 5+ years of experience. Responsibilities include data processing, pipeline development using Python, SQL proficiency with relational databases (PostgreSQL, MySQL, Snowflake), and experience with data pipeline tools (Apache Spark, Kafka, Flink). Familiarity with cloud data solutions (AWS S3, Redshift, Google BigQuery, Azure Data Lake) and CI/CD tools (Git) is crucial. Strong problem-solving, communication, and collaboration skills are essential. Preferred qualifications include NoSQL database experience, containerization technologies (Docker, Kubernetes), big data tools (Hadoop), and cloud certifications.
Must have:
  • Bachelor's/Master's in CS/Engineering
  • 5+ years Data Engineering experience
  • Python for data processing
  • SQL & Relational Databases
  • Data pipeline tools (Spark, Kafka, Flink)
  • Cloud data solutions (AWS, Azure, GCP)
  • CI/CD & Git
Good to have:
  • NoSQL databases
  • Docker, Kubernetes
  • Hadoop
  • Cloud certifications
  • Data visualization tools

Job Details

This is a remote position.

Required Qualifications 

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 

  • 5+ years of professional experience as a Data Engineer or in a related role. 

  • Proficiency in Python for data processing and pipeline development. 

  • Strong knowledge of SQL and experience working with relational databases (e.g., PostgreSQL, MySQL, or Snowflake). 

  • Hands-on experience with data pipeline tools and frameworks (e.g., Apache Spark, Kafka, or Flink). 

  • Familiarity with cloud data solutions such as AWS S3, Redshift, Google BigQuery, or Azure Data Lake. 

  • Experience with CI/CD tools and version control systems like Git. 

  • Strong problem-solving skills and attention to detail. 

  • Excellent communication and collaboration skills. 

 

Preferred Qualifications 

  • Familiarity with NoSQL databases (e.g., MongoDB, Cassandra). 

  • Experience with containerization technologies (Docker, Kubernetes). 

  • Knowledge of big data processing tools and frameworks (e.g., Hadoop). 

  • Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, etc.). 

  • Familiarity with data visualization tools and BI platforms (e.g., Tableau, Power BI)



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