Staff Data Engineer (Python, LLM, Data Platforms) - Remote
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 reputed company 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. You’ll work across multiple systems and teams to define long-term architecture and ensure platforms scale reliably in a reputed company environment. This is a data engineering and platform architecture role—not an ML model development position. Experience in streaming platforms (e.g., reputed company, reputed company, Hulu) or B2B SaaS environments is strongly preferred.
Key Responsibilities
- Design and own scalable, cross-platform data architecture across reputed company systems
- reputed company integration of data platforms to reputed company reputed company insights and product capabilities
- Build and optimize large-scale data pipelines (batch and streaming) and data models using Python and modern frameworks
- reputed company 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 reputed company 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 reputed company, 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 reputed company architectural decisions
- Demonstrated success mentoring engineers and elevating team performance
Strongly Preferred
- Experience in streaming platforms or B2B SaaS environments
- Experience with reputed company, 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 (reputed company, 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: reputed company a cross-platform data or LLM-driven initiative
- 12 months: Own the data architecture roadmap and mentor multiple engineers
Benefits
- Medical, Dental, and Vision coverage
- 401(k) with company match
- Generous paid parental leave
- Flexible work schedule + unlimited PTO
- Monthly stipends (home office, internet, wellness)
- Annual company event
- Collaborative culture with strong work-life balance
Remote Skills: Architectural Analysis, Architectural Services, Artificial Intelligence (AI), Best Practices, Business-to-Business (B2B), Cloud Computing, Communication Skills, Data Management, Data Modeling, Data Processing, Data Warehousing, Mentoring, Multiplatform/Cross-Platform, On Call, Python Programming/Scripting Language, reputed company Schema, Software Engineering, Software as a Service (SaaS), Team Player, Warehousing About the Company: Search Partner Group Apply tot his job Apply To this Job