Senior Data Engineer

OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets.

Role Summary

As a Senior Data Engineer on our Customer Analytics team, you'll own the data foundation behind CRM analytics, measurement, and data science work for major enterprise brands. You'll design and run production pipelines on Google Cloud and decide how data gets modeled, validated, and delivered. Your work turns messy source data into something analysts, data scientists, and clients can trust. When our insights shape how a client spends its marketing budget, your pipelines are the reason those numbers hold up.

The Impact You'll Have

Our clients are large, data-savvy organizations that expect every recommendation to come with proof. Their CRM programs, campaign measurement, and customer segmentation all depend on data you build and maintain. A late or broken feed means a wrong answer in a client meeting. A well-engineered one means faster decisions and measurable ROI.

You'll work between data science, analytics, BI, and client teams. You'll be the person who turns a business question into a data design, and the one who keeps a platform running that serves every discipline on the account.

AI and ML work is moving from experimentation into production across our client environments. You'll help make that happen by building the data plumbing that lets models and agents run reliably inside GCP, instead of stalling in a notebook.

What You'll DoBuild the Pipelines That Power Client Analytics

• Design, build, and maintain batch data pipelines on GCP using BigQuery, Dataform, Cloud Composer/Airflow, and Dataflow. Take a SQL-first approach and build to scale as client data grows.
• Write and optimize complex SQL that keeps BigQuery fast and costs predictable.
• Build external data API integrations on Cloud Run to bring third-party and platform data into a single, usable environment.

Own Data Quality End to End

• Own the validation and cleansing pipelines that catch data problems before they reach a dashboard, a model, or a client.
• Troubleshoot pipeline failures quickly, including tracing issues upstream, and fix root causes so the same failure doesn't come back.

Fuel Data Science and Analytics

• Partner with data scientists and analysts to deliver reliable, well-documented datasets that shorten the path from question to insight.