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Addepar

Cloud-based wealth management data platform

Team Lead Field Engineer

Engineering LeadershipConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listed

About the Job

Requirements

  • At least 8 years of experience in software engineering, data engineering, or forward-deployed technical roles, with demonstrated experience guiding, mentoring, or leading other engineers.
  • Advanced proficiency in Python 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 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.
  • Experience with version control using Git, CI/CD pipelines, and modern software development practices.
  • Ability to balance hands-on delivery with team coordination, feedback, and a commitment to growing people-management skills.
  • Ability to conduct technical presentations and translate complex concepts for technical and non-technical audiences.
  • Ability to prioritize and context-switch across simultaneous client engagements and deliver results that may impact schedules and costs.

Responsibilities

  • Provide functional leadership and daily operational guidance to a team of field engineers while remaining a hands-on technical contributor on complex engagements.
  • Architect, build, and deliver custom integrations, automations, and data pipelines using Addepar APIs, ADX (Databricks), and modern engineering tools.
  • Manage team work allocation and coordinate activities across simultaneous client engagements, delivering results on schedule and in collaboration with cross-functional partners.
  • Guide issue resolution, proactively escalate blockers, and maintain alignment with client and internal stakeholders.
  • Design and implement production-grade solutions to improve client onboarding efficiency, reduce time-to-value, and enable operational scale.
  • Build intelligent automation using AI, large language models, and machine learning to address data transformation, validation, and reconciliation challenges.
  • Serve as technical owner for ADX implementations, designing data infrastructure within Databricks for client data onboarding and analytics.
  • Write and review production-quality Python code for ETL pipelines, API integrations, data validation frameworks, and automation tooling.
  • Translate ambiguous client requirements into flexible, scalable technical solutions through discovery, prototyping, and iterative delivery.
  • Support engineers’ career development through continuous feedback on technical and project execution and mentoring.
  • Identify and drive opportunities to improve tools, workflows, and automation; develop internal frameworks and best practices to accelerate delivery.
  • Collaborate with Product, Engineering, and Services teams to identify productization opportunities and influence the platform roadmap.
  • Act as a technical advisor and trusted partner to clients, proactively identifying opportunities to drive additional value.

About the Company

Addepar

Cloud-based wealth management data platform

Addepar offers a cloud-based wealth management platform that consolidates data for data aggregation, analytics, and reporting. It ingests data from custodians, fund administrators, and broker-dealers to present a single, real-time view with tools for performance, risk, scenario modeling, and automated billing, plus a broad API and hundreds of integrations. It specializes in complex, multi-asset and illiquid portfolios (like private equity and real estate) for high-net-worth clients, with pricing based on assets under management. Its goal is to deliver transparent, data-driven insights and an integrated, scalable system that streamlines portfolio oversight and operations for wealth managers.

Company size
1,001-5,000
Company stage
Series G
Total funding
$872.8M
Headquarters
New York City, New York
Founded
2009

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