Data Solutions Consultant
AddeparPune, IndiaPosted 26 March 2026
Tech Stack
Job Description
Who We Are
Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva and São Paulo.
The Role
As a Data Solutions Consultant, you will support some of Addepar’s complex and high-touch client data implementation projects. You’ll design scalable solutions to transform and integrate clients’ portfolio data into Addepar, and build expertise across both technical and business domains.
You’ll also be among the first members of the Data Solutions team based in India , helping establish our presence in the region while working closely with colleagues across the U.S., U.K., and other global offices. This is a collaborative role offering the opportunity to shape our operating model locally and strengthen how our global teams deliver together.
Beyond client delivery, you’ll also have the opportunity to participate in internal innovation; contributing to automation, tooling, and best practices that enable scale and elevate how we operate globally. This is an individual contributor position for someone who thrives at the intersection of finance, data, and technology, and is excited to make a global impact from India.
Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.
What You’ll Do
Support complex client implementation s: execute data conversion projects to extract, transform, and load historical portfolio data from clients’ legacy systems into Addepar
Build scalable data solutions:
Translate client requirements into flexible, sustainable workflows that enable accurate reporting and analysis, with guidance from senior team members
Contribute to a portfolio of high-impact projects:
Manage multiple concurrent client engagements, prioritizing effectively and driving each to successful completion
Collaborate across teams: Building knowledge of investment-related data and partner closely with Services, Sales, Product, and Engineering to deliver tailored client outcomes
Champion operational excellence:
Identify and lead opportunities to streamline, automate, and improve our delivery processes and workflows
Who You Are
Experienced: 2+ years of experience in technology, finance, or consulting, with a strong record of leading complex data or financial system integration projects
Technical: Proficiency in Python and SQL. You should be comfortable navigating large datasets, streamlining data flows (ETL), and finding ways to automate repetitive manual tasks to improve efficiency. Experience/familiarity with Databricks and API workflows is a plus.
Investment-Savvy:
Technical Translation: Ability to articulate technical architectures to non-technical internal teams, converting technical requirements into clear, actionable business value.
Solutions-Oriented: Curious problem-solver who takes initiative and is developing ownership and accountability in ambiguous environments
Collaborative: Eager to work across teams and functions to deliver measurable impact
Process-Minded: Highly organized, detail-oriented, and continuously looking for ways to improve efficiency and scale
Adaptable: Thrives in a fast-paced environment with evolving priorities and global stakeholders
A Note on Requirements
Don’t check every single box? Apply anyway. We are looking for curious, motivated in ... (truncated, view full listing at source)
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