Mactores - AWS Data Engineer (Senior) (Freelancer)
Requirements
• AWS Data Analytics Specialty Certification • Experience with Agile development methodology • We run a forward-deployed model: engineers embed with delivery teams, own their piece of the outcome, and ship against committed dates. This is a remote freelance engagement, so we'll be straight about the shape: you work project-by-project inside that model, with Aedeon absorbing the repetitive layer so your billed time goes to engineering judgment, not manual validation. You'll work independently, coordinate closely with the engagement team, and your output lands in production systems that customers sign off on. • Life at Mactores • We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work. • 1. Be one step ahead • 2. Deliver the best • 4. Pay attention to the detail • 5. Enjoy the challenge • 6. Be curious and take action • 7. Take leadership • 9. Deliver value • 10. Be collaborative • We would like you to read more details about the work culture on https://mactores.com/careers • The Path to Joining the Mactores Team • At Mactores, our recruitment process is structured around three distinct stages: • Pre-Employment Assessment: • A series of evaluations of your technical proficiency and suitability for the role.
Responsibilities
• Build and maintain data pipelines on Amazon EMR or Amazon Glue that run in production. • Design data models and end-user querying on Amazon Redshift or Snowflake, Amazon Athena, and Presto. • Build and maintain pipeline orchestration with Airflow. • Work with other teams to understand data needs and design the solutions that meet them. • Troubleshoot and optimize pipelines and data models until they hold up under real load. • Write and maintain PySpark and SQL scripts to extract, transform, and load data. • Document and communicate technical decisions to technical and non-technical audiences. • Track new AWS data technologies and judge their impact on the systems we run. • What are we looking for? • Bachelor's degree in Computer Science, Engineering, or a related field. • 3+ years of experience working with PySpark and SQL. • 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue. • 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. • 1+ years of experience building and maintaining pipeline orchestration using Airflow. • Strong problem-solving and troubleshooting skills. • Excellent communication and collaboration skills. • Ability to work independently and within a team environment.
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