Job Description

Position : Data Engineer

Working Hours : M-F, 9:00 AM - 5:00 PM CST

Salary Range : $3,000-$4,000 USD per month,

About the role

You will be responsible for designing, building, and maintaining scalable data

pipelines and infrastructure to support data science and analytics initiatives. Your role will also involve implementing best practices to safeguard data. You will work closely with data scientists, analysts, and other stakeholders to ensure data is accessible, reliable, and structured for complex analyses and machine learning models.

Responsibilities:

• Data Pipeline Development : Design, develop, and maintain scalable data pipelines, ETL (Extract, Transform, Load) processes and architecture to gather data from various sources and integrate it into AWS-based data warehouses or data lakes.
• Data Warehousing : Build and optimize data storage/management solutions (leveraging services such as S3, Redshift, EMR, and Glue for big data processing) to ensure efficient querying and data retrieval.
• Data Quality Management: Implement data quality checks, validation, and cleansing processes to ensure data integrity and reliability.
• Collaboration with Data Scientists: Work closely with data scientists to understand their data requirements and provide them with clean, well-structured data for analysis and modeling.
• Performance Optimization: Optimize data processing workflows and queries to improve performance and reduce latency in data retrieval and analysis.
• Documentation: Document data engineering processes, data models, and system architecture to ensure clarity and maintainability.
• Monitoring and Maintenance: Monitor data pipelines and systems for performance issues, and troubleshoot and resolve any data-related problems that arise.
• Security and Compliance : Ensure that data handling practices adhere to security and compliance standards, including data privacy regulations.
• Tool and Technology Evaluation: Stay updated on emerging data technologies and tools, and recommend improvements or new solutions to enhance data engineering capabilities.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field. An advanced degree is a plus.
• 3-5 years of proven experience as a Data Engineer or in a similar role, with hands-on experience in building and managing data pipelines and data storage solutions
• Technical Skills:
• Strong proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL, SQL Server).
• Experience with big data technologies such as Hadoop, Spark, or Kafka.
• Familiarity with cloud platforms (e.g., AWS preferred) and their data services (S3, Redshift, EMR, Glue, Sagemaker).
• Strong proficiency in programming languages such as Python, Pyspark, Java, or Scala.
• Experience with data warehousing solutions and data modeling.
• Experience with machine learning tools and libraries.
• Certifications: Relevant certifications in data engineering, cloud platforms, or big data technologies are a plus.

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