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Jr. Data Engineer in NJ, NC, TX, CA (Hybrid)

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Jr. Data Engineer

Hybrid (2-3 Days Onsite) - NJ, NC, TX, CA

Contract/ Fulltime

About the Role:

We're seeking a skilled Data Engineer with 4-5+ years of experience to join our dynamic team. In this role, you'll be responsible for designing, implementing, and maintaining our data infrastructure to support our growing analytical and machine learning needs.

Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines for ingesting, processing, and storing large datasets
  • Collaborate with data scientists and analysts to understand data requirements and implement efficient data models
  • Optimize data storage and retrieval systems for performance and cost-efficiency
  • Ensure data quality, integrity, and security across all data systems
  • Implement and maintain data warehousing solutions
  • Develop and maintain documentation for data systems and processes
  • Collaborate with cross-functional teams to integrate data systems with other business applications

Required Qualifications:

  • Bachelor's degree in Computer Science, Information Systems, or a related field
  • 4-5+ years of experience in data engineering or a similar role
  • Strong programming skills in Python and SQL
  • Experience with big data technologies such as Hadoop, Spark, or Hive
  • Proficiency in working with cloud platforms (AWS, Azure, or Google Cloud Platform)
  • Experience with data warehousing and ETL processes
  • Strong understanding of database design and data modeling concepts
  • Excellent problem-solving and analytical skills
  • Strong communication skills and ability to work in a team environment

Preferred Qualifications:

  • Master's degree in a relevant field
  • Experience with real-time data processing systems
  • Knowledge of machine learning and data science concepts
  • Familiarity with data visualization tools (e.g., Tableau, Power BI)
  • Experience with version control systems (e.g., Git)

Tech Stack:

  • Languages: Python, SQL, Java
  • Big Data: Apache Spark, Hadoop, Hive
  • Cloud: AWS (S3, Redshift, EMR), Azure, or Google Cloud Platform
  • Databases: PostgreSQL, MongoDB, Cassandra
  • Data Warehousing: Snowflake, Amazon Redshift
  • ETL Tools: Apache Airflow, Talend
  • Streaming: Apache Kafka, Apache Flink
  • Version Control: Git
  • Containerization: Docker, Kubernetes
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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