Senior Data Engineer

What you'll do

• Build and scale data infrastructure powering targeting, identity, and measurement capabilities
• Implement and optimize ETL/ELT pipelines ensuring operational reliability and documented SLAs
• Onboard new datasets to power targeting capabilities with defined KPIs
• Adopt CI/CD practices to accelerate team velocity using ArgoCD-based deployment pipelines
• Implement and document privacy-compliant data methodologies meeting GDPR/CCPA standards
• Create thorough technical documentation including implementation docs, runbooks, and best practices
• Take operational responsibility for systems including monitoring, iteration, and improvement
• Collaborate actively in design and brainstorming sessions
• Communicate technical decisions clearly to both technical and non-technical stakeholders
• Write and maintain documentation that supports onboarding and knowledge sharing

Requirements

• Deep proficiency in Python and Spark for building and optimizing large-scale data pipelines
• Strong grasp of data structuring for performance and efficiency
• Hands-on experience with Airflow for orchestrating complex data workflows
• Experience with Apache Iceberg for table format management at scale
• Extensive AWS experience including EKS, Docker, and Kubernetes
• Comfortable owning infrastructure deployment and scaling decisions
• CI/CD fluency including ArgoCD, automated testing pipelines, and monitoring via Prometheus
• Familiarity with analytical warehousing in Snowflake or ClickHouse including SQL optimization, cost management, and performance tuning
• Working knowledge of identity, privacy, and targeting methodologies in ad tech
• Preferred: Experience with real-time streaming technologies such as Kafka and Flink
• Preferred: Familiarity with Aerospike or similar low-latency key-value stores

Tech stack