
201 - 500 employees
💸 Finance
🏠 Real Estate
☁️ SaaS
💰 $75M Series C on 2019-11
Finance • Real Estate • SaaS
Juniper Square is a company that provides a comprehensive platform and solutions tailored for private investment partnerships. Founded in 2014, the company focuses on enabling seamless connection and communication between General Partners (GPs) and Limited Partners (LPs) throughout the entire investment lifecycle. Juniper Square's technology is purpose-built to support commercial real estate, private equity, and venture capital firms of all sizes. The platform offers services such as fund administration, fundraising, investor management, compliance, and investor reporting, all aimed at enhancing transparency, data governance, and the overall investor experience.
🕒 May 26
🌐 United States, Canada – Remote
💵 $210k - $260k / year
⏰ Full Time
🔴 Lead
🚰 Data Engineer
👻 Ghost score 38%
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201 - 500 employees
💸 Finance
🏠 Real Estate
☁️ SaaS
💰 $75M Series C on 2019-11
Finance • Real Estate • SaaS
Juniper Square is a company that provides a comprehensive platform and solutions tailored for private investment partnerships. Founded in 2014, the company focuses on enabling seamless connection and communication between General Partners (GPs) and Limited Partners (LPs) throughout the entire investment lifecycle. Juniper Square's technology is purpose-built to support commercial real estate, private equity, and venture capital firms of all sizes. The platform offers services such as fund administration, fundraising, investor management, compliance, and investor reporting, all aimed at enhancing transparency, data governance, and the overall investor experience.
• Design and ship the data normalization, schema mapping, validation, enrichment, and distribution pipeline for a net-new intelligent data warehouse • Write production code as a hands-on individual contributor • Own technical delivery from architecture through deployment, with accountability for reliability, performance, and correctness • Define end-to-end architecture for an AI-native data warehouse serving institutional financial clients • Make technical decisions on schema design, normalization strategies, API exposure patterns, and data distribution • Evaluate and select technologies that ship well and scale sustainably • Design and implement AI output evaluation infrastructure for high-stakes financial data contexts • Build cross-model comparison tooling, deterministic validation checks, and human-in-the-loop review workflows • Use agentic coding tools and LLM-assisted development as the primary workflow • Help evolve AI-accelerated software development practices • Establish coding standards, review practices, and architectural documentation • Define quality standards for a fast-moving engineering team • Mentor engineers and provide technical guidance as the team expands
• 12+ years of software engineering experience with demonstrated Staff-level technical scope and impact • Portfolio of shipped production systems and ability to explain specific technical decisions and personally written code • Strong hands-on experience with data pipeline or data warehouse engineering, including schema design, ETL/ELT patterns, normalization, and API-based data distribution • Production experience building with LLMs, including prompt design, model orchestration, evaluation, and output validation • Daily fluency with AI-assisted and agentic development workflows • Experience with AWS data infrastructure; Redshift experience is a plus • Strong written communication and ability to translate technical design into clear documentation for engineering and product audiences • Ability to evaluate AI-generated code and outputs, including failure modes, regressions, and edge cases • Preferred: experience with RAG pipelines, vector stores, or document extraction systems • Preferred: financial services data background, including fund administration, investment data schemas, or institutional reporting workflows • Preferred: experience building data products or managed data services for external customers • Preferred: prior technical lead or TLM experience on a new or early-stage product team
• Health, dental, and vision care for you and your family • Life insurance • Mental wellness coverage • Fertility and growing family support • Flex Time Off in addition to company-paid holidays • Paid family leave, medical leave, and bereavement leave policies • Retirement saving plans • Allowance to customize your work and technology setup at home • Annual professional development stipend • Equity
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Google Cloud Platform
Kubernetes
Python
PyTorch
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Spark
SQL
Tensorflow