Data Engineer

5 Months ago • 5-8 Years • Data Analysis

Job Summary

Job Description

This remote Data Engineer position requires 5+ years of experience. Responsibilities include data processing, pipeline development using Python, SQL proficiency with relational databases (PostgreSQL, MySQL, Snowflake), experience with data pipeline tools (Apache Spark, Kafka, Flink), and cloud data solutions (AWS S3, Redshift, Google BigQuery, Azure Data Lake). CI/CD tools and Git experience are also necessary. Strong problem-solving, communication, and collaboration skills are essential. The role involves designing, building, and maintaining data pipelines for efficient data ingestion, transformation, and storage.
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
  • Strong problem-solving skills
Good to have:
  • NoSQL database experience (MongoDB, Cassandra)
  • Containerization (Docker, Kubernetes)
  • Hadoop knowledge
  • 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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