Solutions Architect - Hunter
Leads technical strategy and architecture for customer accounts, driving Databricks adoption through scalable data, AI, and real-time analytics solutions. Requires 6+ years of solutions architecture or related experience, strong Python and SQL skills, cloud deployment expertise, and customer-facing technical leadership.
About the job
Responsibilities
- Own end-to-end technical strategy for customer accounts, from discovery through production deployment and consumption growth.
- Lead architecture discussions and design scalable, production-grade solutions spanning data engineering, machine learning and AI, and real-time analytics.
- Advise customer architects, engineering leads, and directors as a trusted technical partner.
- Drive technical wins in competitive scenarios through custom-built solutions and platform differentiation.
- Develop a technical specialization and serve as a subject-matter resource for the team.
- Coordinate DSAs, SSAs, and partners to deliver comprehensive solutions.
- Provide structured feedback on customer requirements and competitive gaps to influence product direction.
Requirements
- 6+ years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role.
- Strong Python and SQL coding skills, including live coding, debugging, and solution building.
- Deep expertise in distributed data systems architecture, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Proficiency with the Databricks Platform or the ability to become proficient rapidly.
- Experience leading architecture discussions with senior technical stakeholders, including whiteboarding, design reviews, and trade-off analysis.
- Production deployment experience on AWS, Azure, or Google Cloud, including infrastructure, security, and governance considerations.
- Track record of driving platform adoption and consumption growth within accounts.
- Excellent communication skills and the ability to translate complex architectures into business value.
- Bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
Nice to Have
- Databricks certifications in data engineering, machine learning, or platform technologies.
- Experience with Snowflake, AWS native services, or Azure Synapse.
- Background in a data/AI company or cloud provider.
- Industry expertise in financial services, healthcare, retail, media, or related domains.
Compensation
- Base salary range: $180,000–$247,500 USD.
- Total compensation may also include an annual performance bonus, equity, and benefits.
Skills
Python, SQL, Databricks, Data Engineering, Machine Learning, Real-Time Analytics, Distributed Systems, Data Pipelines, Streaming, Lakehouse, AWS, Azure, GCP, Snowflake, Azure Synapse
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