Data Engineer

6 Months ago • 5-8 Years • Data Analysis

Job Summary

Job Description

This remote Data Engineer role requires 5+ years of experience. Responsibilities include data processing and pipeline development using Python, SQL, and tools like Apache Spark, Kafka, or Flink. Experience with cloud data solutions (AWS S3, Redshift, Google BigQuery, or Azure Data Lake) and CI/CD tools (Git) is essential. Strong problem-solving, communication, and collaboration skills are needed. Familiarity with NoSQL databases, containerization, Hadoop, and data visualization tools is preferred. The role involves designing, building, and maintaining data pipelines for efficient data processing and analysis.
Must have:
  • 5+ years Data Engineering experience
  • Proficiency in Python & SQL
  • Experience with data pipeline tools (Spark, Kafka, Flink)
  • Cloud data solutions (AWS, Azure, GCP)
  • CI/CD and Git experience
Good to have:
  • NoSQL databases (MongoDB, Cassandra)
  • Containerization (Docker, Kubernetes)
  • Hadoop experience
  • Cloud certifications
  • Data visualization tools (Tableau, Power BI)

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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