Senior Data Platform Engineer

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. 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.

Responsibilities

Design and build platform services, tools, and workflows for contract-driven data publishing and consumption; Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration; Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code; Build tooling that gives product engineers fast feedback before they publish or change data products; Help define how Smartly models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution; 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; Integrate platform metadata into DataHub so engineers can discover data products, understand ownership, trace lineage, and reason about the impact of changes; 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.

Requirements

Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments; Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes; Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance; Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter more; Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows; Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership; Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems without waiting for perfect certainty; Clear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundaries.

Nice to have

DataHub or other data catalog, lineage, or governance systems; Open table formats such as Apache Iceberg, object-store-backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systems; GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems; Data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, or contract testing; Experience supporting analytics, AI/ML, feature-store-style access patterns, or cross-domain product-service integrations; Experience with JVM languages and Python, TypeScript, Go, or Ruby.

Benefits

Inclusive global culture built on trust, transparency, open feedback, and respect for different perspectives; Global impact through technology used by major brands to plan, create, optimize, and understand digital advertising at scale; Wellbeing support, paid holidays, family leave, and sustainable ways of working; Equity options, performance-based rewards, competitive compensation, and career development opportunities; A flexible hybrid workplace that balances office collaboration with focused remote work. At Smartly we work 3 days a week from the office.