Senior Data Engineer

One Magnify 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.

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.

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.

• - Design, build, and maintain batch data pipelines on GCP using Big Query, 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 Big Query 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 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.

• - Partner with data scientists and analysts to deliver reliable, well-documented datasets that shorten the path from question to insight.
• - Work with the data science team on AI/ML integrations in GCP so models can move into production workflows.

• - Lead requirements conversations with client and internal stakeholders, and turn loosely defined asks into clear data designs.
• - Build and maintain dashboards and handle ad-hoc client data requests. Where it makes sense, turn one-off requests into repeatable assets.

• - Use Git, pull request workflows, and CI/CD automated deployments to ship changes safely and often.
• - Raise the team's engineering standards through code reviews and shared best practices.

• - Bachelor's degree in computer science, engineering, information systems, or a related field, or equivalent experience
• - 3+ years of data engineering experience, including production batch pipelines on GCP (Big Query, Cloud Composer/Airflow, Dataflow)
• - Advanced SQL skills, with experience building SQL-first pipelines in…