DataEngineer

Bringg processes over 200 million orders a year through infrastructure that some of the world's largest retailers depend on daily. When the data pipeline works, deliveries land on time at scale. When it doesn't, customers feel it within the hour. We're looking for a Data Engineer to own and evolve the data infrastructure that sits underneath all of it. The pipeline is already built and running at real scale. Your job is to go deeper - embedding data further into the business and pushing the AI/ML layer forward. This isn't a maintenance role. It's an ownership role. In this role, you will: Our data pipelines run faster, scale cleaner, and break less - because you own the architecture and optimization of our BigQuery warehouse end-to-end. High-throughput processing and real-time analytics become possible at a scale we haven't reached yet - because you're shaping the distributed systems that get us there. Data capabilities land in the hands of the people who need them - data scientists, engineers, and product stakeholders from problem to solution, not as a downstream dependency. The infrastructure gets more reliable, more automated, and easier to monitor - because you treat DevOps and MLOps as part of the job, not someone else's problem. AI/ML models move from development into production and stay there - not handed off, but owned through the full deployment lifecycle. What you Bringg Must have: 4+ years building high-scale data pipelines and managing cloud data warehouses (BigQuery strongly preferred) Hands-on experience with Kafka, CDC tools (Estuary or similar), and pipeline orchestration (Airflow, dbt) Deep command of SQL and NoSQL ecosystems - Postgres, Redis, Elastic Solid backend development skills with strong OOP/OOD fundamentals Exposure to MLOps and production AI/ML model deployment Experience with AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) Comfortable working independently with minimal structure — you drive things, you don't wait for