Technical Solutions Architect

What You’ll Do

• Deploy directly to client sites (virtual or in-person) to architect, build, and deliver custom integrations, automations, and data pipelines using Addepar's APIs, ADX (Databricks), and modern engineering tools
• Design and implement production-grade solutions that dramatically improve client onboarding efficiency, reduce time-to-value, and enable operational scale
• Build intelligent automation leveraging AI, LLMs, and machine learning to solve complex data transformation, validation, and reconciliation challenges
• Serve as the technical owner for ADX implementations, designing robust data infrastructure within Databricks to streamline client data onboarding and analytics
• Translate ambiguous client requirements into flexible, scalable technical solutions through deep discovery, prototyping, and iterative delivery
• Write production-quality Python code for ETL pipelines, API integrations, data validation frameworks, and automation tooling
• Lead technical workstreams end-to-end, from requirements gathering through production deployment, owning outcomes and client success
• Collaborate with Product, Engineering, and Services teams to identify opportunities for productization and influence platform roadmap
• Develop internal tools, frameworks, and best practices that accelerate delivery across the broader team
• Effectively set, manage, and communicate technical expectations with both client stakeholders and internal cross-functional teams
• Prioritize and context-switch effectively across simultaneous client engagements, seeing each through to successful completion
• Act as a technical advisor and trusted partner to clients, proactively identifying opportunities to drive additional value

Who You Are

• Minimum 3+ years of experience in software engineering, data engineering, or forward-deployed technical roles
• Advanced proficiency in Python with experience building production-grade applications, APIs, and data pipelines
• Strong understanding of REST APIs, authentication patterns, and integration architecture
• Hands-on experience with Databricks, Spark, and distributed data processing frameworks
• Proficiency in SQL and experience working with large-scale datasets across relational and NoSQL databases
• Experience designing and implementing ETL/ELT pipelines for complex data transformations
• Familiarity with AI/ML tools and experience implementing LLM-driven automation solutions
• Strong understanding of financial data domains including portfolio management, performance analytics, and multi-asset class portfolios
• Exceptional problem-solving abilities with a solutions-oriented mindset and bias for action
• Outstanding communication skills with the ability to translate technical concepts for non-technical audiences
• Proven ability to thrive in ambiguous, fast-paced environments while maintaining high-quality standards
• Experience with version control (Git), CI/CD pipelines, and modern software development practices