Job Description & Details
This is a hands-on, high-ownership role where you will act as both a data engineer and a solutions engineer for enterprise chemical companies. If you are tired of waiting for Jira tickets and want to own complex data migrations from scoping to go-live, this gig offers the autonomy to run projects end-to-end.
What You'll Actually Be Doing
You will take a signed SOW and drive the entire integration lifecycle, typically over six-month project sprints. Your day-to-day involves talking directly with customer IT teams, mapping messy enterprise data like SAP raw-material lot numbers, and building custom connectors on a standardized harness. You won't just be coding in a silo; you'll balance weekly customer syncs, guide domain experts on data transformation best practices, and leverage AI coding tools to accelerate builds while using your engineering judgment to review the output.
The Core Tech Stack
You need absolute fluency in Python or Node.js, deep experience building robust ETL pipelines, and a solid grasp of AWS infrastructure and RESTful or event-driven architectures. Because the company is migrating its stack, prior hands-on experience with Databricks is a major plus. You must also be comfortable orchestrating complex system integrations and talking shop with enterprise IT stakeholders.
Interview Expectations
Expect the hiring team to test your system design chops with a scenario where a legacy SAP database has inconsistent schemas and your custom connector is dropping payloads mid-sync. They want to see how you troubleshoot distributed bottlenecks under pressure. You will also likely be grilled on your client-facing communication style, specifically how you push back on scope creep from a non-technical enterprise stakeholder without derailing the project timeline.
Application Advice
Your resume needs to scream end-to-end ownership rather than ticket-closing. Highlight metrics from past data migrations, emphasize your direct experience talking to enterprise customers, and make sure keywords like Python, AWS, ETL, and Databricks are prominent to easily clear the ATS.