Job Description & Details
This is a heavy-hitting 12-month contract for a Data Integration Architect who can walk into a messy enterprise ecosystem and clean up the data flow. You will be acting as the bridge between legacy systems and modern cloud architecture, making sure data moves reliably without breaking downstream pipelines. If you enjoy designing end-to-end data strategies rather than just writing single queries, this gig is worth your time.
What You'll Actually Be Doing
Your primary responsibility is architecting robust ETL pipelines and integration patterns between heavy enterprise platforms like SAP, Oracle HR, Salesforce, and your cloud warehouse. You'll spend a lot of time defining source-to-target mappings, setting up inbound and outbound data flows, and establishing strict data governance standards. Expect to work closely with engineering teams to ensure that data transformation logic is clean, scalable, and doesn't bottleneck analytics.
The Core Tech Stack
To survive here, you need deep, production-level fluency in AWS Glue, DBT, and Snowflake. This isn't just about knowing how to spin up a resource; you need to understand how these three tools work in concert to handle massive enterprise data volumes efficiently. The company relies on this stack to unify disparate feeds like MAS data and payroll, so your ability to optimize DBT models and Glue jobs for cost and performance will directly determine your success on the project.
Interview Expectations
When you get on the technical screen, expect them to grill you on how you handle schema evolution and breaking changes when integrating third-party systems like Salesforce or SAP. The hiring manager isn't looking for a textbook definition of ETL; they want to hear a war story about a time a data pipeline broke in production and how you fixed it using Snowflake and DBT. Another favorite topic will be data governance—be prepared to explain how you enforce quality and lineage across complex cloud architectures.
Application Advice
Your resume needs to scream enterprise data architecture, not just basic SQL scripting. Make sure terms like AWS Glue, DBT, Snowflake, SAP integration, and source-to-target mapping are front and center, as the ATS will definitely be scanning for them. Don't just list your past job titles; highlight specific instances where you designed enterprise-wide data flows from scratch and managed large-scale data migrations.