Principal Data Platform Engineer (Swedish Ad Platform)

Sigmasoftware2; Poland; On-site; PLN 300,000 - 600,000; Full time

Job summary

Sigmasoftware2 is seeking a senior Data Platform Architect to lead the design and operation of a production-grade data platform in Poland. You will shape data flows from event storage to analytical products, select technologies for orchestration and storage, and define scalable models across domains.

You will guide engineers, enforce data contracts and governance, and optimize performance and costs while collaborating with leadership and cross-functional teams.

Qualifications

• 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.
• 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.

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.

Skills

Distributed data

Event-driven

Iceberg lakehouse

SQL proficiency

Python

Java/Scala

Spark/Flink/Trino

AWS

CI/CD

Data contracts

Data quality

Data governance

Tools

Apache Iceberg

Spark

Flink

Trino

Airflow

CI/CD tooling

Job description

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.