Staff Data Engineer (Python, LLM, Data Platforms) Remote Remote (U.S. Only)
$220,000 $240,000 + Full Benefits About the Opportunity An international media and digital analytics organization is seeking a Staff Data Engineer (formally titled Staff Engineer Data Engineering) to lead the evolution of its large-scale data platforms.
This is a senior, high-impact individual contributor role focused on data architecture, cross-platform integration, and building LLM-powered data products. Youll work across multiple systems and teams to define long-term architecture and ensure platforms scale reliably in a complex environment.
This is a data engineering and platform architecture rolenot an ML model development position.
Experience in streaming platforms (e.g., Spotify, Netflix, Hulu) or B2B SaaS environments is strongly preferred. Key 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
Required Qualifications
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
Strongly Preferred
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
Technical Environment
Cloud data warehouses (Snowflake, BigQuery, or similar)
Data processing & orchestration (Spark, Airflow)
Streaming platforms (Kafka or equivalent)
Batch and real-time data pipelines
Cloud-native / containerized environments (Kubernetes a plus)
What Success Looks Like
First 90 days: Deliver an architectural assessment and identify integration opportunities
6 months: Lead a cross-platform data or LLM-driven initiative
12 months: Own the data architecture roadmap and mentor multiple engineers