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 Lead Data Engineer, you'll lead projects within OneMagnify's data engineering team end-to-end — staying hands-on in design, architecture, and standards rather than handing them off. It's roughly 60% leadership, 40% technical build. You'll work closely with strategy and analytics to keep the data layer behind our client work fast, reliable, and built to scale. The Impact You'll Have
The platforms you build power what OneMagnify's enterprise clients can do with their data — real-time personalization, customer segmentation, and the clean foundation analytics teams need for advanced modeling. When a client wants cross-channel marketing that responds to customer behavior in the moment, your architecture makes that possible.
You'll be the technical anchor connecting data engineering with analytics, creative, and strategy on complex projects — the coordination that OneMagnify's integrated delivery model depends on. Along the way, you're setting the technical bar: modern architecture patterns, tighter workflows, and platforms that stay secure and aligned with where clients are headed.
What You'll Do
Lead Projects End-to-End
Lead data engineering projects from the ground up, owning design and architecture decisions
Set the engineering standards the team builds against — and hold your own work to the same bar
Stay hands-on in the code on key projects, mentoring engineers through reviews and pairing
Architect and Build Data Infrastructure
Design and implement ETL/ELT pipelines that hold up under real production load
Build advanced database solutions in Oracle Cloud Database and PostgreSQL — database architecture, query refinement, stored procedures
Develop cloud-native data solutions on Google Cloud Platform that scale with client demand
Raise the Engineering Bar
Set the standard for maintainability, testing, and documentation, and own resolution of the hardest technical problems
Bring CI/CD and infrastructure-as-code into delivery, working alongside DevOps to keep releases fast and clean
Monitor system performance and get ahead of issues before clients see them
Own Delivery
Run sprint planning and manage timelines so complex projects land on time and at quality
Coordinate dependencies across engineering, operations, and client-facing teams
Weigh in on hiring and onboarding decisions as the team scales
What You'll Need
7+ years in data engineering, database development, or a related technical subject area
3+ years leading or managing engineering teams, proven in mentoring engineers and delivering results
Deep expertise in Oracle’s cloud-based database systems development, including PL/SQL, performance tuning, and cloud-native features
Advanced PostgreSQL skills — schema design, query tuning, indexing, and database administration
Hands-on experience with various services within Google's cloud ecosystem such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, or Cloud Composer
Strong Python and SQL, with a track record of writing clean, production-quality code
Experience with Git, CI/CD pipelines, and agile development
Strong problem-solving instincts for complex, multi-source data environments
Clear communicator who can work across technical and non-technical teams
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience
Future-Ready Skills (Nice to Have)
Experience with Azure services (Data Factory, Synapse Analytics, Azure SQL Database, Data Lake Storage)
Hands-on work with…