6 months ago
New York, NY, USAMid Level
Base Salary
$95k - $149k/yr
Responsibilities
- Deploy to client sites virtually or in person to architect, build, and deliver custom integrations, automations, and data pipelines.
- Design and implement production-grade solutions that improve client onboarding efficiency, reduce time-to-value, and enable operational scale.
- Build AI, LLM, and machine-learning-driven automation for data transformation, validation, and reconciliation.
- Own ADX implementations and design data infrastructure within Databricks for client onboarding and analytics.
- Translate ambiguous client requirements into scalable technical solutions through discovery, prototyping, and iterative delivery.
- Write production-quality Python for ETL pipelines, API integrations, data validation frameworks, and automation tooling.
- Lead technical workstreams from requirements gathering through production deployment and own client outcomes.
- Collaborate with Product, Engineering, and Services teams to identify productization opportunities and influence the platform roadmap.
- Develop internal tools, frameworks, and best practices to accelerate delivery across the team.
- Set, manage, and communicate technical expectations with client stakeholders and internal cross-functional teams.
- Act as a technical advisor and trusted partner by identifying opportunities to create additional client value.
Requirements
- At least 3 years of experience in software engineering, data engineering, or forward-deployed technical roles.
- Advanced Python proficiency and 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 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.
- Experience with Git, CI/CD pipelines, and modern software development practices.
- Strong problem-solving, communication, adaptability, and client-engagement abilities.
- Ability to work independently, manage ambiguity, prioritize across simultaneous engagements, and maintain high-quality standards.
- Legal authorization to work in the United States without current or future visa sponsorship and authorization to begin work on the first day.
Tech Stack
Categories
Forward DeployedSolutions Engineering
About Addepar
Addepar builds a SaaS platform for wealth and investment management firms to aggregate portfolio, market and client data, analyze holdings, and produce client reporting. The company sells software and data integrations used across investment operations, with APIs and a broad partner ecosystem to plug into other tools. Founded in 2009 and headquartered in New York, it is privately held and used by over a thousand firms globally to manage trillions in assets.