AWS Data Engineer (Senior)
✨ AI Summary
Mactores, an AWS modernization firm using agent-native delivery, is hiring a Senior AWS Data Engineer in Mumbai (fully remote). You'll build production data pipelines with PySpark, SQL, EMR, Glue, Redshift, Snowflake, Athena, Presto, and Airflow. Requires 3+ years PySpark/SQL, 2+ years EMR/Glue, 2+ years data modeling/querying, and 1+ years Airflow. Perks include a casual culture focused on shipping outcomes, with a structured 3-stage hiring process.
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 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.
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