Staff Data Engineer
Staff Engineer, Data Engineering
About the Role:
We are seeking a highly experienced Staff Engineer, Data Engineering to provide technical leadership across a complex and evolving data ecosystem. This role is ideal for a hands-on technical leader who thrives at the intersection of data architecture, large-scale distributed systems, and AI-powered product development. As a Staff Engineer, you will play a critical role in shaping the long-term data strategy, driving architectural alignment across multiple platforms, and enabling the next generation of data and AI-driven products. You will partner closely with Engineering, Product, and Machine Learning teams to build scalable systems that support real-time analytics, audience intelligence, and advanced data applications. This is an individual contributor role with significant influence across teams, technologies, and business initiatives.
What You'll Do:
- Design, own, and evolve large-scale data architecture across multiple products and platforms
- Lead technical strategy for integrating disparate data systems into a cohesive ecosystem
- Architect and deliver scalable data pipelines, streaming infrastructure, and warehouse solutions
- Drive AI and backend infrastructure initiatives, including LLM-powered product capabilities and data foundations for AI workloads
- Establish best practices for data modeling, governance, observability, reliability, and performance
- Partner with Product, Engineering, and ML teams to translate business requirements into scalable technical solutions
- Evaluate and implement emerging AI, machine learning, and generative AI technologies
- Provide mentorship and technical guidance to engineers across the organization
- Influence engineering standards, architectural decision-making, and roadmap prioritization
- Participate in production support and on-call responsibilities for critical systems
What Success Looks Like: Within your first year, you will:
- Drive alignment of data architecture across multiple teams and platforms
- Improve system scalability, reliability, and maintainability
- Deliver production-ready AI-enabled data capabilities
- Establish higher engineering standards and best practices across the organization
- Strengthen collaboration between Data Engineering, Product, and ML teams
- Enable the successful integration of data products and services across the business
Required Qualifications:
- 8+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture roles
- Proven success in a senior individual contributor or technical leadership position
- Strong expertise in Python and modern backend development practices
- Experience designing and operating large-scale data platforms and architectures
- Hands-on experience building production data pipelines and distributed systems
- Deep understanding of data modeling, data warehousing, and data platform design
- Experience with Kafka or similar event-streaming technologies
- Experience with modern cloud data warehouses such as Snowflake or similar technologies
- Hands-on experience building and deploying products that leverage Large Language Models (LLMs) or Generative AIStrong communication skills with the ability to explain architectural decisions to both technical and non-technical stakeholders
- Demonstrated track record of mentoring engineers and elevating team capabilities
Preferred Qualifications:
- Experience with BigQueryFamiliarity with Kubernetes and containerized environments
- Experience with real-time streaming architectures and event-driven systems
- Background integrating platforms, products, or data systems across organizations
- Experience partnering closely with Product teams to define and deliver customer-facing capabilities
- Passion for technical mentorship, engineering culture, and organizational impact
- Technologies You'll Work WithPythonKafkaSnowflakeSparkElasticsearchCloud-based data platforms
- Generative AI and LLM technologies
- Real-time data processing and analytics systems