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.

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.

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.

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.

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