Technical Solutions Architect
Architects and builds custom integrations, automations, and data pipelines using Addepar APIs and Databricks for client onboarding. Requires 3+ years experience with Python, ETL, Spark, SQL, and AI/ML tools in financial data contexts.
About the job
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
Skills
Python, Databricks, Spark, SQL, REST APIs, ETL, ELT, Git, CI/CD, AI/ML, LLMs
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