AWS Data Engineer (Associate)

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 role sits in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters.

Customers come to us with pipelines nobody trusts, metrics nobody agrees on, and warehouses that stall every new business question.

Because Aedeon handles the repetitive layer source discovery, schema mapping, validation harnesses - you won't spend your early career grinding through spreadsheet audits.

You'll spend it writing code that reaches production and learning judgment from engineers who own cutovers. Data quality isn't a checkbox here; it's the product. What you will do? Write efficient PySpark and Amazon Glue code that ships to production.

Write SQL in Amazon Athena and Amazon Redshift. Pick up new technologies and techniques and put them to work on real business problems. Work across engineering and business teams to build data products and services people actually use.

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 the data products that fix that - working with business leads, analysts, and data scientists to understand the domain, then shipping pipelines and models that hold up in production.
• What you will do?
• Work across engineering and business teams to build data products and services people actually use.
• Deliver projects with the team and land customer updates on time.
• Deep understanding of the Dataframe API and the transformation functions supported by Spark 2.7+.
• You will be preferred if you have Prior experience in working on AWS EMR, Apache Airflow Certifications AWS Certified Big Data – Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer Understanding of DataOps Engineering How we work?
• Engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally.

Required Skills and Qualifications

• 1 to 3 years of experience in Apache Spark, PySpark, and Amazon Glue.
• 2+ years of experience writing ETL jobs using PySpark and SparkSQL.
• 2+ years of experience with SQL queries and stored procedures.
• You will be preferred if you have Prior experience in working on AWS EMR, Apache Airflow Certifications AWS Certified Big Data – Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer Understanding of DataOps Engineering 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.

Work Location and Schedule

This role is listed as Remote USA with location information shown as Remote USA. The employment type is Full Time.

About the Company

Mactores is the organization connected with this listing. USA Jobs Today displays this opportunity for job discovery only, so applicants should verify company details, application instructions, and eligibility on the official employer website.