AWS Data Engineer (Senior) (Freelancer)

Mactores is the agent-native AWS modernization firm. Most modernization work doesn't ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores' founders' sister company, which absorbs the repetitive 60–70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.

This is a senior freelance role in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters. Customers come to us after a data program has stalled — pipelines nobody trusts, warehouses nobody runs new workloads on, a modernization that produced diagrams instead of production systems.

Aedeon handles automated source discovery, schema mapping, lineage extraction, and parallel-run validation. You take the work that needs a senior engineer's judgment: pipeline builds on EMR and Glue, data models for Redshift, Snowflake, Athena, and Presto, Airflow orchestration, and the troubleshooting that gets a system stable enough to cut over. Freelance here means real delivery work on real engagements — not staff augmentation into someone else's backlog.

What you will do?

• 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.

You are preferred if you have

• AWS Data Analytics Specialty Certification
• Experience with Agile development methodology

How we work?