Staff Data Engineer - AI-Native Data Platform

Juniper Square; United States; Remote; USD 210,000 - 260,000; Full time

Benefits offered by this job

Health, dental, and vision

Flexible time off

Annual development stipend

Job summary

Juniper Square is building a next-generation intelligent data platform for private markets. As Staff Software Engineer, Data, you will own the design and hands-on delivery of core pipeline components—schema mapping, normalization, validation, enrichment, and distribution—to downstream systems.

You will write production code daily, set technical standards, mentor engineers, and shape an AI-native SDLC. This role blends data engineering with applied AI, requiring strong architectural judgment and

Qualifications

• 12+ years of software engineering with staff-level impact.
• Shipped production systems with data pipelines.
• Experience with data warehouses/ETL patterns.
• Production experience with LLMs and AI tooling.
• Proficient in AWS data infrastructure and Redshift.
• Strong written communication for engineering docs.
• Ability to evaluate AI-generated code and outputs.

Responsibilities

• Design and ship data normalization and schema mapping pipelines.
• Write production code as a hands-on contributor.
• Own architecture from design through deployment.
• Define AI-native data warehouse architecture for financial clients.
• Set coding standards and architectural documentation.
• Mentor engineers and guide team expansion.

Skills

Staff-level scope

Data pipeline

LLMs in production

AWS data infra

Communication

AI code evaluation

Tools

Redshift

Job description

Juniper Square is building a next-generation intelligent data platform for private markets. As Staff Software Engineer, Data, you will own the design and hands-on delivery of core pipeline components—schema mapping, normalization, validation, enrichment, and distribution—to downstream systems.

You will write production code daily, set technical standards, mentor engineers, and shape an AI-native SDLC. This role blends data engineering with applied AI, requiring strong architectural judgment and