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Salary
$31k – $83k per year (Estimated)
Location
In office
Employment
Full-Time
Overview
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Impact
Profile match

We are seeking an experienced Data Engineer to design, implement, and maintain our data infrastructure and pipelines. The ideal candidate will have a strong background in data engineering, big data technologies, and cloud platforms. You will work closely with data scientists, analysts, and other stakeholders to ensure efficient and reliable data processing and storage solutions.

Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines and ETL processes
  • Implement and optimize data storage solutions, including data warehouses and data lakes
  • Collaborate with data scientists and analysts to understand data requirements and provide efficient data access
  • Ensure data quality, consistency, and reliability across all data systems
  • Develop and maintain data models and schemas
  • Implement data security and access control measures
  • Optimize query performance and data retrieval processes
  • Evaluate and integrate new data technologies and tools
  • Mentor junior data engineers and provide technical leadership
  • Collaborate with cross-functional teams to support data-driven decision-making

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • 4-8 years of experience in data engineering or related roles
  • Strong programming skills in Python, Java, or Scala
  • Extensive experience with big data technologies such as Hadoop, Spark, and Hive
  • Proficiency in SQL and experience with both relational and NoSQL databases
  • Experience with cloud platforms (AWS, Azure, or GCP) and their data services
  • Knowledge of data modeling, data warehousing, and ETL best practices
  • Familiarity with data visualization tools (e.g., Tableau, Power BI)
  • Experience with version control systems (e.g., Git) and CI/CD pipelines
  • Strong problem-solving skills and attention to detail
  • Excellent communication and collaboration skills
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