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.

Enterprise SAP data is where data platform modernization goes to stall. The tables are cryptic, the semantics live in someone's head, and the extraction tooling punishes wrong choices months later. This role exists because getting that data out cleanly and back in usably, takes an engineer who knows SAP from the inside.

As our SAP Data Engineer, you'll own the SAP side of a modern data pipeline for enterprise customers running SAP on AWS. You'll design and ship the extraction layer that lifts data out of SAP HANA into S3 cleanly and incrementally, and you'll build the BW / BW4HANA load path that takes curated data back into the warehouse for business users to query. Agents absorb the repetitive discovery and validation work around you; the judgment calls which extraction tool per source, how the semantics map, what the S3 contract looks like, are yours.

You'll work alongside a PySpark engineer who owns the transformation layer on EMR, meeting them at the S3 boundary. You'll be the SAP voice on customer calls, and the person engineering counts on when raw SAP tables need to become datasets a business analyst can trust. This is a freelance engagement, remote from India, embedded with a customer team through cutover.