Technical Lead (Data)

About Juniper Square: Private financial markets are one of the largest, most complex, and most underserved corners of global investment finance. Our mission at Juniper Square (junipersquare.com) is to unlock their full potential. We are the trusted Operations Partner for over 2,300 General Partners (GPs), unifying modern technology, asset data layers, and institutional fund administration services into a single integrated platform that helps investment firms move faster, make better decisions, and scale with absolute precision. With $300B+ under administration and 700,000+ Limited Partners (LPs) on platform, we have built the scale to match our immense ambition. And with JunieAI, our purpose-built generative AI platform, we are actively reimagining how private markets operate, embedding deep intelligence across every investment workflow. Founder-led since 2014, backed by $350M+ in institutional venture funding, and over 1,000 employees strong, we are building a company designed to shape global finance for decades to come.

Position Overview

We are seeking a highly analytical, connection-obsessed, and systems-minded Technical Lead (Data) to anchor our scaling Data Engineering group under a permanent, full-time remote engagement framework based anywhere across India. Operating as the primary architectural authority and technical compass for our data platforms, you will step up to claim true individual operational and strategic accountability over evolving our internal and external analytics products. Shifting completely away from routine script execution, basic query optimization, or isolated backend maintenance, you will run an active high-scale extraction pipeline, complex data modeling, and full-stack application engineering laboratory—partnering face-to-face with product pods, core software architects, data scientists, and customer-facing engineering teams. This position requires a seasoned full-stack data veteran with 7-11 years of deep building history who structures highly relational schemas and scalable pipelines fluidly natively using Python frameworks, designs reusable interactive data components cleanly natively utilizing ReactJS and TypeScript, and orchestrates modern generative AI application boundaries confidently within highly performant cloud data warehouses.

Key Responsibilities

• Data Infrastructure Architecture: Architect, implement, and maintain highly scalable data models, relational database systems (Postgresql preferred), and complex ETL/ELT pipelines processing raw data from diverse sources cleanly natively utilizing Python engineering methodologies.
• Full-Stack Data Product Engineering: Design and execute modern web application layers, building performant backend web services using FastAPI and RESTful/GraphQL APIs while developing modular, reusable UI components using ReactJS and TypeScript.
• Technical Guidance & Code Quality: Act as the core domain expert regarding full-stack data architecture, introducing new tooling paradigms and establishing strict code review, data cataloging, and access control policies to guarantee business confidentiality.
• AI Tooling and Agentic Integration: Investigate, deploy, and scale advanced workflow capabilities natively utilizing Python scripts, integrating pattern structures such as tool-calling agents, planning/execution loops, and Retrieval-Augmented Generation (RAG) to accelerate application capabilities.
• Analytics Product Commercialization: Master application schemas and data dictionaries, translating complex underlying database states into clear, scannable customer-facing data visualizations and business intelligence products.
• Data Warehouse Optimization: Design scalable structural mappings to interact seamlessly with advanced analytical data warehouses including Snowflake, Amazon Redshift, or Google BigQuery.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical full-stack software development history.
• A minimum of 7 to 11 years of verified professional experience building automated ETL/ELT pipelines, distributed data layers, and analytics backends from scratch.
• Masterful programmatic command over backend application development natively utilizing Python , accompanied by direct history constructing RESTful/GraphQL APIs via FastAPI.
• Mandatory, expert-tier capability authoring responsive web interfaces using ReactJS and TypeScript, including a proven track record designing reusable UI components.
• Deep operational fluency handling complex relational databases, database modeling, and optimization tasks (Postgresql and cloud services like AWS RDS highly preferred).
• Proven capability navigating enterprise business intelligence or visualization environments (such as Looker, Tableau, PowerBI, or Mode Analytics).
• Demonstrated history translating multi-source relational datasets into actionable architectural narratives and communicating technical choices clearly to stakeholders.
• Location Context: Position is open to experienced software leaders resident in India executing a remote work-from-home track (with optional physical office access available in Mumbai and Bangalore).

Preferred Strategic Indicators (Nice to Have)

• Prior experience operating inside a rapid startup environment or global hyper-growth Financial Technology (FinTech) software enterprise.
• Familiarity with open-source or commercial data cataloging and metadata governance networks (such as OpenMetadata).
• Familiarity with recent automated developer productivity tools and LLM prompt engineering mechanisms to elevate pipeline velocity.

What We Offer

• Vetted, High-Scale FinTech Leadership Blueprint: A premium, highly competitive regional corporate base salary matched directly to your 7-11 years of technical engineering depth, plus comprehensive performance bonuses.
• The spectacular professional canvas to lead and shape the data engineering standards for an elite $300B+ asset administration platform.
• Profound work-from-home remote parameters offering a digital-first virtual framework, absolute schedule execution autonomy, and zero localized commuting friction.
• A flat, transparent developer culture that embraces open technical debate, ownership-driven execution, and high engineering standards.
• Comprehensive health, wellness, and technical resources engineered to empower distributed engineering groups globally.