Senior Data Platform Engineer

About this role

<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 bespoke point-to-point integrations.</li> </ul> <h2>What we are looking for</h2> <ul> <li>Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments.</li> <li>Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes.</li> <li>Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance.</li> <li>Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter more.</li> <li>Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows.</li> <li>Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership.</li> <li>Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems without waiting for perfect certainty.</li> <li>Clear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundaries.</li> </ul> <h2>Useful experience, but not required</h2> <ul> <li>DataHub or other data catalog, lineage, or governance systems.</li> <li>Open table formats such as Apache Iceberg, object-store-backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systems.</li> <li>GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems.</li> <li>Data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, or contract testing.</li> <li>Experience supporting analytics, AI/ML, feature-store-style access patterns, or cross-domain product-service integrations.</li> <li>Experience with JVM languages and Python, TypeScript, Go, or Ruby.</li> </ul> <h2>What we offer you</h2> <p>At Smartly, we offer a place where you can do meaningful technical work while growing with a global team.</p> <ul> <li>Inclusive global culture built on trust, transparency, open feedback, and respect for different perspectives.</li> <li>Global impact through technology used by major brands to plan, create, optimize, and understand digital advertising at scale.</li> <li>Wellbeing support, paid holidays, family leave, and sustainable ways of working.</li> <li>Equity options, performance-based rewards, competitive compensation, and career development opportunities.</li> <li>A flexible hybrid workplace that balances office collaboration with focused remote work. At Smartly we work 3 days a week from the office.</li> </ul> <h2>About Smartly</h2> <p>Smartly is an advertising technology company helping brands create, manage, optimize, and understand digital advertising across major media platforms. Our engineering organization builds