Senior Solutions Architect
Leads complex enterprise architecture engagements, consumption strategy, and executive customer relationships for data and AI platforms. Requires 8+ years of solutions architecture or senior technical pre-sales experience, expert Python and SQL skills, and deep enterprise data architecture expertise.
About the job
Responsibilities
- Drive technical and consumption strategy for complex customer engagements, influencing platform adoption and revenue growth.
- Own senior-level technical relationships and advise enterprise customers on data and AI strategy.
- Lead complex architecture engagements involving multi-workload platforms, enterprise migrations, real-time systems, and AI/ML at scale.
- Serve as an expert on the Databricks Platform and mentor team members.
- Develop competitive strategies and position Databricks against incumbent and emerging platforms.
- Orchestrate cross-functional teams, including DSAs, SSAs, partners, and product teams, to deliver enterprise-grade solutions.
- Coach and develop junior solutions architects on technical depth, customer engagement, and use-case prioritization.
- Contribute to field-engineering thought leadership through customer-facing content, workshops, and community engagement.
Requirements
- 8+ years of experience in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role.
- Expert coding proficiency in Python and SQL; Spark/PySpark experience preferred.
- Deep expertise in enterprise data architecture, distributed systems, streaming and real-time systems, lakehouse design patterns, data governance, and cloud-native platforms.
- Expert Databricks Platform knowledge, or equivalent depth in competing platforms with demonstrated ability to learn quickly.
- Recognized technical specialization in areas such as real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions.
- Track record of driving consumption growth and platform adoption in large accounts.
- Executive presence and ability to influence Directors, VPs, and C-level stakeholders on data and AI strategy.
- Experience leading competitive displacements and complex enterprise evaluations.
- Strategic thinking that connects technical architecture decisions to business outcomes and revenue impact.
- Bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
Nice to Have
- Databricks certifications.
- Experience at Databricks, Snowflake, AWS, Google, Microsoft, or a leading data and AI company.
- Published thought leadership, including blogs, conference talks, or open-source contributions.
- Industry vertical expertise with executive-level domain credibility.
Skills
Python, SQL, Spark, Pyspark, Distributed Systems, Streaming, Lakehouse, Data Governance, Cloud-Native Platforms, Databricks, Machine Learning, Artificial Intelligence, Enterprise Architecture, Data Architecture, Competitive Strategy
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