Staff Data Engineer
United States of America
Full Time
4 hours ago
$220,000 - $240,000 USD
No H1B
Key skills
PythonAILLMData EngineeringAnalyticsSnowflakeBigQueryKafkaKubernetesSaaSMentoringCommunication
About this role
Search Partner Group, LLC is an international media and digital analytics organization seeking a Staff Data Engineer to lead the evolution of its large-scale data platforms. This senior role focuses on data architecture, cross-platform integration, and building LLM-powered data products, ensuring platforms scale reliably in a complex environment.
Responsibilities:
- Design and own scalable, cross-platform data architecture across complex systems
- Lead integration of data platforms to enable unified insights and product capabilities
- Build and optimize large-scale data pipelines (batch and streaming) and data models using Python and modern frameworks
- Develop production-grade Python code for data processing, platform services, and LLM-enabled workflows
- Design and deliver LLM-powered applications and data products
- Establish best practices for data modeling, pipeline design, and system observability
- Mentor engineers and raise the technical bar across teams
- Translate business needs into clear, scalable architectural decisions
- Contribute to architecture reviews, roadmap planning, and on-call support
Requirements:
- 8+ years of experience in data engineering or data architecture
- Proven experience working in complex, multi-system or multi-team environments
- Strong Python expertise (5+ years of hands-on, production-level development)
- Experience building LLM-powered systems or data-driven AI applications in production
- Deep experience with large-scale data architecture (pipelines, modeling, warehousing)
- Strong communication skills — able to clearly articulate architectural decisions
- Demonstrated success mentoring engineers and elevating team performance
- Experience in streaming platforms or B2B SaaS environments
- Experience with Snowflake, BigQuery, or similar cloud data warehouses
- Familiarity with Kafka or real-time streaming architecture
- Experience with Kubernetes or containerized environments
- Track record of cross-platform or cross-division data integration
- Passion for mentorship, teaching, and building engineering culture