Data Engineer (Intern)
Posted 2,017 days ago, which is unusual. The employer's own board was still carrying it when we last read it, 1 hour ago.
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2017d ago
The date the source published, not the day we noticed it (2021-03-08). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Mumbai
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $6,750–7,250/mo
Middle 50% of 9 listings that do state pay — Engineering · all levels · India · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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lever employer's own board first seen 14d ago · last seen 1h ago
The listing
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 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.