Data Operations Specialist

At Smollan Technologies, we provide a unified, technology-driven suite of products that redefines how businesses handle data. We don’t just build applications; we build cloud-native, high-throughput engines that turn raw unstructured media into predictive intelligence. Our Engineering team is no different. We are moving away from monolithic backends and rigid systems, flipping the switch on next-gen applied AI and event-driven data platforms. By centralising our server-heavy architectures, inference job orchestration, and rich web interfaces within automated cloud workflows, we are transforming complex technical infrastructure into a forward-thinking strategic asset.

Our vision for our Data Operations Specialist is to carry day-to-day technical accountability for high-volume data management workflows, custom integrations, and the data processing pipelines that power our platforms. This isn't just about routine processing; it’s about deep-diving into end-to-end data structures, securing and onboarding complex new data sources, and executing custom setups with deterministic accuracy. The ideal candidate is a forward-thinking analyst who is not only fluent in SQL, reporting tools, and data warehousing concepts, but actively excited about troubleshooting intricate data challenges, driving operational pipeline efficiencies, and bridging the gap between external data providers and internal engineering teams.

What you will do

• Manage Custom & Special Setups: Spec, design, and execute custom data setups while building and maintaining technical relationships with key data providers, distributors, and clients.
• Drive High-Volume Data Processing: Accurately process and manage data using specialised internal data platforms to ensure delivery within strict service-level agreements.
• Resolve Complex Technical Issues: Troubleshoot and resolve complex data processing and pipeline failures independently before joint escalations are needed.
• Collaborate Cross-Functionally: Work directly with Client Success, Data Engineers, Data Integration, and Data Visualisation teams to translate operational requirements into scalable systems.
• Optimise Operations: Identify, recommend, and implement workflow enhancements and continuous process improvements across the data management cycle.
• Mentor & Lead: Train, mentor, and guide junior and trainee operations analysts on data management standards and system tools.