Senior Data Platform Engineer

<p>We are looking for a&nbsp;<strong>Senior Data Platform Engineer</strong> to join the <strong>Data Platform</strong> at Smartly!</p> <p>Smartly is building the standard path for governed data sharing across product services, analytics, and AI/ML. The Data Platform team owns the contracts, control mechanisms, publication paths, catalog metadata, lifecycle rules, lineage, permissions, and runtime building blocks that make reusable data safe and practical at scale.</p> <p>This is a role for someone who wants to shape a platform early, while working on concrete production problems from the start. Smartly already has the production systems, Kafka backbone, PostgreSQL databases, analytical consumers, and AI/ML use cases that need a better data foundation. The challenge is to turn that reality into a standard path that engineers actually want to use.</p> <p>Our first milestone is focused: centrally managed publishing tables in service-owned PostgreSQL databases, captured through Debezium CDC into Kafka, and registered in DataHub with ownership, lifecycle, lineage, and impact-analysis metadata. Longer-term, the platform expands toward self-service data products, governed materialisations, durable shared state, and reusable data across Smartly’s operational and analytical systems.</p> <p>This is not a role where you only maintain an existing reporting pipeline. You will help design and build the platform path that other engineering teams use when they publish and consume shared data.</p> <h2>What you will do</h2> <ul> <li>Design and build platform services, tools, and workflows for contract-driven data publishing and consumption.</li> <li>Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration.</li> <li>Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code.</li> <li>Build tooling that gives product engineers fast feedback before they publish or change data products.</li> <li>Help define how Smartly models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution.</li> <li>Operate and improve the CDC runtime model, including Kubernetes workloads, source-specific isolation, offsets, schema history, heartbeats, signal channels, lag visibility, replay, resnapshotting, and recovery.</li> <li>Integrate platform metadata into DataHub so engineers can discover data products, understand ownership, trace lineage, and reason about the impact of changes.</li> <li>Work with product, infrastructure, data engineering, analytics, and AI/ML teams to make the standard path easier and safer than