Data Engineer (Intern)
Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Mar 8, 2021. Mactores scores D on the Alion truth index.
This internship is an apprenticeship in data platform modernization the pillar of our work where legacy warehouses get retired and data platforms reach production on AWS. You'll write real pipeline code on real projects, working with business leads, analysts, and data scientists to understand the domain, then with engineers to build data products that make decisions better.
Here's the honest framing: you're learning the agent-native craft, not owning cutover. Agents handle much of the repetitive discovery and validation work that used to fill junior engineers' days, which means your time goes further into Spark, ETL design, and understanding why data quality decisions matter to the business. If you care about the quality of the metrics a business runs on, and you want your solutions to scale to bigger questions, this is the seat.
What you will do?
- Write efficient code in the technology chosen for the project - Spark or Apache Beam, for example.
- Explore new technologies and learn new techniques to solve business problems creatively.
- Collaborate across engineering and business teams to build better data products and services.
- Deliver projects with the team and keep customers updated on time - shipping on schedule is a habit you'll build early here.
What we are looking for?
- Exposure to Apache Spark.
- Exposure to ETL concepts using pySpark and SparkSQL.
- Exposure to SQL queries and stored procedures, and the appetite to work on challenging projects with a mentor-oriented leader.
You will be preferred if you have
- Prior experience in working on AWS EMR, Apache Airflow
- AWS Certified Big Data - Specialty certification, Azure Certification, Snowflake Certification
- Cloudera or Hortonworks Certified Big Data Engineer
- Understanding of DataOps Engineering
How we work?
Mactores delivers through agents plus forward-deployed engineers. Aedeon, the agent platform we deploy, does the repetitive majority source discovery, schema mapping, validation harnesses while engineers make the architecture and cutover calls. As an intern you work inside that model from day one: you'll see how a data platform actually reaches production, and you'll learn to work with agents as tooling rather than treating them as a threat or a magic trick. The engineers who grow fastest here are the ones who master that combination.