Principal Data Platform Engineer

Company Description Join a greenfield initiative focused on building a next-generation AI-first data platform for a global AdTech ecosystem. We are looking for a Principal/Staff Data Platform Engineer who will drive architectural decisions, establish engineering standards, and shape the foundation for scalable analytics and AI capabilities. As part of Sigma Software, you will collaborate with experienced engineering teams and contribute to a platform designed around immutable event-driven architecture, governed data contracts, and modern lakehouse principles. This role is ideal for a Principal-level engineer who enjoys solving complex distributed systems challenges and influencing platform strategy from day one. We offer the opportunity to work on large-scale international products, collaborate with highly skilled professionals, and contribute to a technically ambitious environment with long-term growth potential. CUSTOMER Our Customer is a Sweden-based AdTech company specializing in advanced self-serve advertising platforms that automate direct transactions between advertisers and major global publishers. Their solutions improve transparency and operational efficiency in digital advertising and are trusted by globally recognized brands including TripAdvisor, Bloomberg, The Washington Post, Opera, and Dow Jones. The company processes millions of advertising transactions worldwide and is actively investing in AI-driven data capabilities. PROJECT The project focuses on building a modern data platform from the ground up with an emphasis on immutable event streams, governed canonical models, semantic layers, and scalable analytics infrastructure. The platform will support analytical workloads, operational data products, AI applications, and future customer-facing data experiences. As a Principal / Staff Data Platform Engineer, you will own key architectural decisions, define scalable engineering standards, and help deliver the first production-ready version of the platform in a high-scale AdTech environment. Key Technologies: Apache Iceberg, Spark, Flink, Trino, AWS, Python, Scala, Java, CI/CD, Infrastructure as Code Job Description Lead the technical design and architecture of a modern enterprise-scale data platformDefine scalable data flows from Iceberg-based event storage into analytical and operational data productsEvaluate and select technologies for orchestration, transformation, querying, serving, and storageDesign reusable canonical entities and data models across advertising, campaigns, inventory, billing, and customer domainsEstablish scalable engineering patterns for batch and near-real-time processingBuild reliable and observable data pipelines for high-volume AdTech workloadsImplement data quality, lineage, observability, and reconciliation capabilitiesCollaborate with Platform Engineering teams to introduce CI-enforced data contracts and governance standardsDefine tenant isolation, access control, and regional data boundary strategiesEstablish standards for testing, deployment automation, schema evolution, and versioningOptimize platform performance, scalability, and infrastructure costsMentor engineers and contribute to engineering excellence across the teamPartner closely with leadership and cross-functional stakeholders Qualifications 8+ years of experience designing and operating production-grade data platformsStrong expertise in distributed data systems and high-volume event-driven architecturesDeep understanding of modern lakehouse architectures and Apache IcebergAdvanced SQL skills and production experience with Python, Java, Scala, or similar languagesExperience with distributed processing and query technologies such as Spark, Flink, or TrinoStrong knowledge of data modeling, partitioning strategies, and performance optimizationProven experience building batch and near-real-time data pipelinesHands-on experience with AWS cloud infrastructureStrong understanding of CI/CD pipelines, Infrastructure as Code, and production observabilityExperience implementing data contracts, schema evolution, and data quality frameworksAbility to make pragmatic architectural decisions in greenfield environmentsUpper-Intermediate or higher English levelStrong communication and technical leadership skills WILL BE A PLUS Experience in AdTech or other high-volume event-processing domainsExperience designing multi-tenant SaaS data architecturesFamiliarity with semantic layer technologiesExperience supporting both analytics and ML/AI workloadsUnderstanding of privacy regulations and data residency requirements Additional Information 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.