Principal / Staff Data Platform Engineer in ad-tech

Описание: DanAds is building an AI-first data foundation where governed events from product and platform systems are transformed into trusted data models, governed data products, analytics, AI capabilities, and customer-facing data experiences. Задачи: Lead the technical design of DanAds' new data platform; Define how data moves from the Iceberg-based event layer into downstream analytical and operational data products; Evaluate and select technologies for querying, transformation, orchestration, storage, and serving; Design canonical entities and reusable data models across advertising, inventory, campaigns, orders, billing, and customers; Establish scalable patterns for batch and near-real-time processing; Design for high-volume ad-tech workloads; Build data quality, observability, lineage, and reconciliation into the platform; Work with Platform Engineering on CI-enforced data contracts between source systems and Data & AI; Establish tenant isolation, access controls, and regional data boundaries; Define engineering standards for testing, deployments, versioning, and schema evolution; Own performance and cost optimization of the data platform; Mentor other data engineers as the team grows; Act as a senior technical partner to the Head of Data & AI and Platform Engineering; Deliver the first production data foundation within the first six months; Document clear architectural decisions; Establish enforceable contracts for events entering the data platform; Create and test core canonical entities; Make data quality and lineage observable; Enable other engineers to contribute without understanding every implementation detail. Требования: Significant experience designing and operating production data platforms; Strong experience with distributed data systems and high-volume event data; Deep understanding of modern lakehouse architectures and open table formats such as Apache Iceberg; Strong SQL and production experience in Python, Java, Scala, or similar; Experience with distributed processing and query technologies such as Spark, Flink, Trino, or comparable platforms; Strong understanding of data modeling, partitioning, performance, and storage design; Experience building batch and near-real-time data pipelines; Experience with cloud infrastructure, preferably AWS; Strong understanding of CI/CD, infrastructure-as-code, and production observability; Experience with data contracts, schema evolution, and data-quality frameworks; Ability to make architectural decisions without over-engineering the first version; Nice to have: Ad-tech or similarly high-volume event-processing experience, multi-tenant SaaS data architecture, semantic layers, data platforms supporting analytics and ML/AI workloads, privacy, residency, and regulated data environments. Условия: No conditions specified