Principal Data Platform Engineer – Swedish Ad Platform

This is a fully remote position, open to applicants in Germany, +1 more country.

📋 Description

• Oversee the technical design and architecture of a contemporary enterprise-scale data platform.

• Develop scalable data flows from Iceberg-based event storage into both analytical and operational data products.

• Assess and select technologies for orchestration, transformation, querying, serving, and storage.

• Create reusable canonical entities and data models spanning advertising, campaigns, inventory, billing, and customer domains.

• Establish scalable engineering patterns for both batch and near-real-time processing.

• Construct reliable and observable data pipelines capable of handling high-volume AdTech workloads.

• Implement capabilities for data quality, lineage, observability, and reconciliation.

• Collaborate with Platform Engineering teams to introduce CI-enforced data contracts and governance standards.

• Define strategies for tenant isolation, access control, and regional data boundaries.

• Establish standards for testing, deployment automation, schema evolution, and versioning.

• Optimize platform performance, scalability, and infrastructure costs.

• Mentor engineers and contribute to engineering excellence within the team.

• Work closely with leadership and cross-functional stakeholders.

• Deliver the initial production-ready version of the platform.

• Establish architectural decisions, enforceable event contracts, tested canonical entities, and observable data quality and lineage.

⛳️ Requirements

• A minimum of 8 years of experience in designing and operating production-grade data platforms.

• Extensive expertise in distributed data systems and high-volume event-driven architectures.

• Profound understanding of modern lakehouse architectures and Apache Iceberg.

• Advanced proficiency in SQL.

• Production experience with Python, Java, Scala, or similar programming languages.

• Familiarity with distributed processing and query technologies such as Spark, Flink, or Trino.

• Strong knowledge of data modeling, partitioning strategies, and performance optimization techniques.

• Proven track record in building both batch and near-real-time data pipelines.

• Practical experience with AWS cloud infrastructure.

• Solid understanding of CI/CD pipelines, Infrastructure as Code, and production observability.

• Experience in implementing data contracts, schema evolution, and data quality frameworks.

• Capability to make pragmatic architectural decisions in greenfield environments.

• Upper-Intermediate or higher proficiency in English.

• Strong communication skills and technical leadership abilities.

🏝️ Benefits

• Opportunity for remote work.

• Potential for long-term career growth.

• Collaboration with experienced and highly skilled professionals.

• Chance to work on large-scale international products.

• A technically ambitious work environment.