AWS Data Engineer (Senior)
Job Overview
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.
Job Description
Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.
This is a senior role in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters, at meaningfully lower engagement cost than traditional data consulting.
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 own what agents can't: target architecture, data model decisions, pipeline design under real constraints, and the calls that make a cutover safe.
You'll build with PySpark and SQL on EMR and Glue, model for Redshift, Snowflake, Athena, and Presto, orchestrate with Airflow and your work will reach production, not a slide deck. 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.
Key Responsibilities
- 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.
- You'll build with PySpark and SQL on EMR and Glue, model for Redshift, Snowflake, Athena, and Presto, orchestrate with Airflow and your work will reach production, not a slide deck.
- What you will do?
- Build and maintain data pipelines on Amazon EMR or Amazon Glue that run in production.
- Build and maintain pipeline orchestration with Airflow.
- 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue.
- 1+ years of experience building and maintaining pipeline orchestration using Airflow.
- Senior engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally fixed dates, with Mactores absorbing overage cost for delays inside our control.
Required Skills and Qualifications
- 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.
- You are preferred if you have AWS Data Analytics Specialty Certification Experience with Agile development methodology How we work?
- Managerial Interview: The hiring manager engages with you in multiple discussions, 30 minutes to an hour each, covering technical skills, hands-on experience, leadership potential, and communication.
USA Jobs Today role summary
Role Summary
AWS Data Engineer (Senior) at Mactores is a remote United States position and is listed as Full Time.
Mactores is the agent-native AWS modernization firm.
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Application Checklist
- Review the stated qualifications, including: Bachelor's degree in Computer Science, Engineering, or a related field. + years of experience working with PySpark and SQL.
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Work Location and Schedule
This role is listed as Remote USA with location information shown as Remote USA. The employment type is Full Time.
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