Job Description & Details
This is a heavy-duty data integration lead role where you'll be architecting and optimizing massive data pipelines using Talend and Snowflake. If you enjoy untangling legacy data flows and turning them into high-performing cloud architectures, this long-term contract offers a chance to make a massive impact on enterprise-scale data infrastructure.
What You'll Actually Be Doing
You will spend your days designing, developing, and deploying complex ETL/ELT pipelines while collaborating with stakeholders to align data engineering strategies with business goals. Expect to spend a lot of time tuning Snowflake query performance, troubleshooting data ingestion bottlenecks in Talend, and mentoring junior engineers on best practices for cloud data warehousing.
The Core Tech Stack
You need absolute mastery over Talend for data integration and Snowflake for cloud data warehousing. The team relies heavily on advanced SQL, performance tuning, and robust CI/CD deployment strategies for data pipelines. If you can't walk into an interview and explain how you optimize a slow-running Snowflake virtual warehouse or handle schema drift in Talend, you're going to struggle here.
Interview Expectations
Expect the hiring manager to hit you with a scenario where a massive nightly Talend load fails halfway through and blocks downstream reporting in Snowflake, asking you to walk through your exact debugging and recovery steps; they want to see your real-world incident management and graceful error-handling experience, not textbook answers. You'll also likely be quizzed on Snowflake's architecture, specifically how you leverage clustering keys and zero-copy clones to solve concurrency and performance issues under heavy loads.
Application Advice
Skip the generic bullet points on your resume and make sure your experience explicitly highlights large-scale migrations to Snowflake using Talend. Weave in keywords like ETL architecture, performance tuning, data modeling, and CI/CD directly into your project descriptions so you easily clear the initial automated keyword filters.