Senior Data Engineer, AWS Data Platform

Hiring immediately. We are looking for someone who can start now or on a short notice period.

Experience: 5+ years in data engineering

Type: Full-time

Location: Remote (India)

Working hours: 5:30 PM to 2:30 AM IST. Hard requirement, not a preference.

Stack: AWS (S3, Glue, Redshift, Athena, Lambda, SNS/SQS, SES, RDS Postgres), Delta Lake, Apache Airflow, a metadata-driven ingestion framework, SQL, Python, GitHub, GitHub Copilot

About the role

We run a modern data platform on AWS for an enterprise client in the payments space. Data moves from a raw landing zone through curated Delta layers into Redshift, driven by a metadata framework rather than hand-written one-off pipelines, across separate non-production, UAT and production environments.

Alongside the platform sits a live customer-facing service: SLA breach detection built on SNS, SQS, Lambda and Athena, with configuration-driven checks and notifications going to real customers. New customers are onboarded onto it continuously.

You would own both halves.



This is a hands-on engineering role, and it is also the role that talks to the client's stakeholders directly rather than through a proxy.

This is an immediate opening on a live project, so we are moving quick on interviews and offers. If you are available on a short notice period, say so in your application.

A note on the hours. The shift is a genuine part of this role rather than a formality. Your day overlaps almost entirely with a US-based stakeholder group. It suits some people well and it is worth being sure it works for you before applying.

What you will own

The SLA alerting service. Config-driven breach checks, the detection engine on Lambda and Athena, customer notifications, onboarding new customers onto the platform, and the parts people skip: DLQs, replay, idempotency, and not sending four thousand emails when a config goes wrong.

Source onboarding into Redshift. Taking a new source from SFTP, SAP,

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