REQUIRED QUALIFICATIONS:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in data engineering or a similar role.
• Strong hands-on experience with AWS data services (e.g., EMR, Glue, Lambda, Step Functions, S3, Redshift).
• Advanced proficiency in Python for scripting and automation.
• Solid experience with Unix/Linux shell scripting.
• Strong command of SQL and experience with relational databases.
• Proficiency with GitHub for version control and collaboration.
• Experience with Terraform and/or AWS CloudFormation for infrastructure-as-code.
• Experience working in Agile/Scrum environments.
• Excellent verbal and written communication skills.
• Proven ability to contribute to high-level solution design and architecture discussions.
• AWS Certification (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect, or equivalent).

PREFERRED QUALIFICATIONS:

• Exposure to machine learning pipelines or data science workflows.
• Experience with data governance, security, and compliance best practices
  Job Type: Contract
  Pay: $65.00 per hour
  Expected hours: 8 per week

Application Question(s):

• What is your total year of experience?
• Do you have 3+ years of experience in data engineering or a similar role?
• Do you have experience with Python for scripting and automation?

Work Location: In perso

KEY RESPONSIBILITIES:

• Design, build, and maintain scalable, secure, and efficient data pipelines using AWS services such as Glue, Lambda, Step Functions, S3, Redshift, EMR, and Data Pipeline.
• Develop robust Python scripts for data ingestion, transformation, and automation.
• Write and optimize complex SQL queries for ETL and analytics workflows.
• Operate in Unix/Linux environments for scripting, automation, and system-level data operations.
• Participate in Agile ceremonies (daily stand-ups, sprint planning, retrospectives) and contribute to iterative delivery of data solutions.
• Collaborate with cross-functional teams to gather requirements and translate them into high-level architecture and design documents.
• Communicate technical concepts clearly through documentation, presentations, and stakeholder meetings.
• Implement monitoring, logging, and alerting for data pipelines to ensure reliability and performance.
• Apply DevOps best practices using GitHub, Terraform, and CloudFormation for infrastructure automation and CI/CD.