Sr. Solution Architect
On-siteNew York, United States or Washington, United States
Job Summary
Partner with sales and marketing teams to identify business challenges and design scalable geospatial data solutions leveraging the Wherobots platform. Lead architectural onboarding sessions, collaborate with engineering teams to design optimal data pipelines and inference workflows, and support customers in deploying best practices for geospatial data lifecycle management. Deliver impactful product demonstrations, create reusable field enablement assets, and troubleshoot advanced technical issues as an escalation point. Author technical content including Jupyter notebooks, blog posts, and solution architecture templates while representing the company at technical events and engaging with open-source communities.
Required Qualifications
- Bachelor's degree in a related field (e.g., Computer Science, Engineering, Geography related field or equivalent experience)
- Experience and or familiarity with spatial data and spatial data analysis
- Minimum 5+ years experience in a pre-sales and post-sales technical support role
- Strong understanding of complete data analytics stack and workflow, from ETL to data platform design to BI and analytics tools
- Excellent communication and presentation skills with the ability to articulate complex ideas and concepts to both technical and non-technical stakeholders
- Strong skills in databases, data warehouses, and data processing
- Problem-solving and analytical abilities
- Customer-focused with a commitment to client satisfaction
- Fosters a collaborative and supportive team dynamic
- Apache Spark
- Lakehouse Database technology (e.g. Iceberg, Glue, PostgreSQL)
Desired Qualifications
- Apache Sedona
- Experience and track record of success selling data and/or analytics software to enterprise customers; includes proven skills in identifying key stakeholders, winning value propositions and compelling events
- Data Science/AI experience across a variety of platforms and industries
- Extensive knowledge of and experience with large-scale database technology
- Familiarity and experience with downstream consumption patterns (e.g. BI tools, customer access patterns, etc.)
- Proven success at enterprise software start-ups
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