Senior Data Platform Engineer

Smartly.io; Helsinki; Hybrid; EUR 110,000 - 140,000; Full time

Benefits offered by this job

Career development programs

Bonus programs and equity options

Generous healthcare packages

Job summary

Smartly.io is seeking a Senior Data Platform Engineer to shape a data platform used across product services, analytics, and AI/ML. You will design platform services and workflows for contract-driven data publishing, ensuring reliable, scalable data foundations for engineers.

You’ll work with PostgreSQL, Debezium, Kafka, and DataHub, building the first production data publishing path and advancing the platform toward self-service data products and governance at scale.

Qualifications

• Strong experience designing and operating data platform components.
• Ability to translate architecture into concrete production systems.
• Experience with data contracts, schema registries, and governance.

Responsibilities

• Design and build platform services, tools, and workflows for contract-driven data publishing and consumption.
• Build production paths for PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration.
• Create GitOps-style workflows for contracts, schemas, ownership, lifecycle, and policy metadata.

Skills

Distributed systems

Technical leadership

Problem solving

Tools

PostgreSQL

Kafka

Debezium

DataHub

Kubernetes

CI/CD tooling

Python

Go

Job description

• We are looking for a Senior Data Platform Engineer to join the Data Platform at Smartly!
• 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
• 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
• 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
• 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

Benefits

• Career development opportunities, bonus programs and annual performance reviews
• Hybrid working model, with the option to work abroad for up to 30 days
• Company equity options program
• Paid holidays, OOO time and family leaves
• Generous healthcare packages and mental health services

Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performanceExperience with Kafka, event streaming, CDC, Debezium, or adjacent data‑movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter moreAbility to turn ambiguous architectural direction into practical increments, make trade‑offs explicit, and deliver useful production systems without waiting for perfect certaintyExperience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self‑service workflowsFamiliarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownershipStrong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data‑intensive environmentsClear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundariesDeep understanding of distributed systems trade‑offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modesOpen table formats such as Apache Iceberg, object‑store‑backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systemsDataHub or other data catalog, lineage, or governance systemsGitHub Actions, policy‑as‑code, infrastructure‑as‑code, controllers, operators, or reconciliation‑based systemsExperience supporting analytics, AI/ML, feature‑store‑style access patterns, or cross‑domain product‑service integrationsData contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field‑level metadata, or contract testingExperience with JVM languages and Python, TypeScript, Go, or Ruby