- 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
- 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
WILL BE A 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.