Senior Software Engineer, Data (AI)

About Juniper Square

Private markets are one of the largest, most complex, and most underserved corners of global finance. Our mission at Juniper Square is to unlock their full potential. We’re the Operations Partner trusted by 2,300+ GPs, unifying technology, data, and fund administration services into a single platform that helps GPs move faster, make better decisions, and scale with precision. With $300B+ under administration and 700,000+ LPs on platform, we’ve built the scale to match our ambition. And with JunieAI, our purpose-built AI platform, we’re reimagining how private markets operate, embedding intelligence across every workflow. Founder-led since 2014, backed by $350M+ in funding, and now 1,000+ employees strong, we’re building a company designed to shape the future of private markets for decades to come.

Our culture is built for people who want to do ambitious, meaningful work alongside exceptionally talented teammates. We think like owners, move with urgency, and take pride in solving hard problems that truly matter to our customers and the future of private markets. We believe the best ideas come from open debate, deep collaboration, and diverse perspectives, which is why we believe transparency is the default and feedback makes us stronger. If you’re energized by high standards, rapid growth, and the opportunity to help define a category at a pivotal moment, come join us!

Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.

About your role

Juniper Square’s Data Platform team owns the foundational data infrastructure that powers reporting, analytics, and data access across the company. The team built and operates the data fabric – a real-time streaming data layer built on Kafka, Flink, and Redshift – that serves as the company’s unified data access layer and underpins in-app reporting for customers. The team is now expanding that foundation with a self-service data catalog, governance tooling, and a self-service ingestion and transformation platform built on dbt and Airflow.

As a Senior Software Engineer on the Data Platform team, you will own the delivery of meaningful components of this infrastructure – building and extending systems for data ingestion, transformation, cataloging, lineage, and observability. Since these are self-service tools with significant admin surface, you will also be comfortable with full stack development as you build and maintain these surfaces. You will write production code every day, contribute to technical architecture discussions, and help scale a platform that serves both internal teams and end customers.

This role is for someone who executes with high craft and speed, is fluent in agentic development as a first-class part of their workflow, and cares deeply about the reliability and usability of the systems they build.

What you'll do

Build and Extend Core Data Infrastructure

• Design and ship production-quality enhancements to the data fabric platform, including streaming ingestion pipelines (Kafka, Flink), Redshift-based storage and query layers, and data distribution to consuming teams and products

• Contribute to the self-service ingestion and transformation platform – enabling domain teams to publish data models and analysts to create aggregations without blocking on data engineering

• Extend and maintain the CI/CD pipeline for dbt transformations, including validation frameworks that prevent regressions as the model library grows

Own Data Catalog and Governance Capabilities

• Build and operate the data catalog platform, enabling stakeholders across the company to discover available data, understand business context, search by keyword, and trace lineage

• Implement integrations between the catalog and upstream systems – dbt, query history, data publishers – to keep lineage and metadata accurate and current

• Contribute to governance tooling that ensures data quality, compliance, and observability across the platform as usage scales

Build and Operate with AI-Native Practices

• Use agentic coding tools and LLM-assisted development as your primary workflow – this is how the entire team operates

• Critically evaluate AI-generated code for correctness, edge cases, and regressions before shipping

• Bring and share strong opinions on how to use AI tooling effectively across the full software development lifecycle

Drive Quality, Reliability, and Observability

• Build and maintain monitoring, alerting, and observability tooling that keeps data pipelines healthy and issues detectable before they affect consumers

• Write well-tested, performant code and participate actively in code reviews, raising the technical bar for the team

• Produce clear technical documentation for the systems you build, enabling self-service adoption by internal teams

Collaborate Across Engineering and Product

• Partner with your engineering manager, peer engineers, and data consumers (domain teams, analysts, product engineers) to translate requirements into well-scoped technical work

• Contribute to cross-functional alignment on data contracts, schema standards, and ingestion patterns – helping prevent duplicated logic and siloed implementations across teams

• Develop deep domain knowledge of private markets data – fund administration, investment workflows, reporting requirements – to build infrastructure that serves real business needs

Qualifications

Required

• 4–7 years of software engineering experience, with a track record of owning and shipping production data systems end-to-end

• Hands-on experience building and operating data pipelines or data warehouse infrastructure: streaming or batch ingestion, ETL/ELT patterns, schema design, query optimization

• Experience with AWS data infrastructure; Redshift experience strongly preferred

• Comfort working across the data stack – from pipeline logic and storage to APIs and observability tooling

• Production experience building with LLMs – integrating models into real systems, not just experimentation

• Fluency with AI-assisted and agentic development workflows; you use these tools daily and evaluate their output critically

• Strong written communication – able to document technical decisions clearly for both engineering and non-technical audiences

Preferred

• Experience with streaming data technologies such as Kafka or Flink

• Experience with dbt (dbt-core preferred) and workflow orchestration tools such as Airflow

• Familiarity with data catalog or data governance platforms – open source (e.g. OpenMetadata) or commercial

• Experience building backend services using Python/FastAPI and designing and implementing scalable RESTful and GraphQL APIs

• Experience authoring modern web applications using ReactJS and TypeScript and designing reusable UI components and scalable frontend architecture.

• Background in financial services data – familiarity with fund administration, investment data schemas, or institutional reporting workflows is a meaningful differentiator

• Experience building self-service data platforms or developer-facing data tooling for internal consumers

•Familiarity with data lineage, data contracts, or metadata management patterns at scale

Compensation

Compensation for this position includes a base salary, equity, and a variety of benefits. The U.S. base salary range for this role is $185,000 – $225,000 USD. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable.

Benefits include:

• 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

Your recruiter can provide additional details about compensation and benefits

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