Principal Data Platform Engineer (Swedish Ad Platform)

Responsibilities

• Lead the technical design and architecture of a modern enterprise-scale data platform
• Define scalable data flows from Iceberg-based event storage into analytical and operational data products
• Evaluate and select technologies for orchestration, transformation, querying, serving, and storage
• Design reusable canonical entities and data models across advertising, campaigns, inventory, billing, and customer domains
• Establish scalable engineering patterns for batch and near-real-time processing
• Build reliable and observable data pipelines for high-volume AdTech workloads
• Implement data quality, lineage, observability, and reconciliation capabilities
• Collaborate with Platform Engineering teams to introduce CI-enforced data contracts and governance standards
• Define tenant isolation, access control, and regional data boundary strategies
• Establish standards for testing, deployment automation, schema evolution, and versioning
• Optimize platform performance, scalability, and infrastructure costs
• Mentor engineers and contribute to engineering excellence across the team
• Partner closely with leadership and cross-functional stakeholders

Qualifications and Requirements

• 8+ years of experience designing and operating production-grade data platforms
• Strong expertise in distributed data systems and high-volume event-driven architectures
• Deep understanding of modern lakehouse architectures and Apache Iceberg
• Advanced SQL skills and production experience with Python, Java, Scala, or similar languages
• Experience with distributed processing and query technologies such as Spark, Flink, or Trino
• Strong knowledge of data modeling, partitioning strategies, and performance optimization
• Proven experience building batch and near-real-time data pipelines
• Hands-on experience with AWS cloud infrastructure
• Strong understanding of CI/CD pipelines, Infrastructure as Code, and production observability
• Experience implementing data contracts, schema evolution, and data quality frameworks
• Ability to make pragmatic architectural decisions in greenfield environments
• Upper-Intermediate or higher English level
• Strong communication and technical leadership skills

Plus

• Experience in AdTech or other high-volume event-processing domains
• Experience designing multi-tenant SaaS data architectures
• Familiarity with semantic layer technologies
• Experience supporting both analytics and ML/AI workloads
• Understanding of privacy regulations and data residency requirements

What success looks like within your first six months

• The first production data foundation is running.
• Clear architectural decisions have been made and documented.
• Events entering the data platform have enforceable contracts.
• Core canonical entities exist and are tested.
• Data quality and lineage are observable.
• Other engineers can contribute without needing to understand every implementation detail.