Senior Software Engineer, Juniper Square

• 4–7 years of software engineering experience, with a track record of shipping production systems end-to-end
• Strong backend engineering fundamentals - backend services, data pipelines, and API design; we will ask you to walk through systems you personally built
• Hands-on experience with data pipeline or data warehouse engineering: ETL/ELT patterns, schema design, normalization, and data distribution
• Production experience building with LLMs - prompt design, model integration, and output validation in real systems
• Fluency with AI-assisted and agentic development workflows; you use these tools daily and evaluate their output critically
• Experience with AWS data infrastructure; Redshift experience a plus
• Strong written communication - able to document technical decisions clearly for engineering and product audiences
• Ability to critically evaluate AI-generated code and outputs, including identifying failure modes and regressions

Desirable

• We are building a next-generation intelligent data platform for private markets - a greenfield initiative that will reshape how financial data is ingested, normalized, validated, enriched, and distributed across a complex ecosystem. This is a foundational role on a small, high-caliber team working at the intersection of modern data engineering and applied AI
• As a Senior Software Engineer, Data, you will own the end-to-end delivery of core pipeline components: schema mapping, data normalization, validation, enrichment, and distribution to downstream systems
• You will write production code every day, work closely with Staff engineers on meaningful architectural decisions, and help build the technical standards and practices the broader team will grow into
• 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 wants the challenge of building something genuinely new
• Deliver Core Data Pipeline Components
• Build and ship production-quality implementations of data normalization, schema mapping, validation, enrichment, and distribution pipelines for a net-new intelligent data warehouse
• Write clean, well-tested, performant code across backend services, data pipeline logic, and API integrations
• Take end-to-end ownership of features from design through deployment, with accountability for correctness and reliability in production Contribute to Technical Architecture
• Work closely with Staff engineers to shape the architecture of a modern, AI-native data warehouse serving institutional financial clients
• Bring thoughtful input on schema design, normalization approaches, and API patterns - and execute those decisions with precision
• Identify and raise technical risks early; propose and implement solutions rather than waiting to be directed 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 - shipping quality output regardless of how it was produced
• Contribute to the team's evolving practices around AI-accelerated development and testing Support Data Quality and Reliability
• Build and maintain data validation checks, monitoring, and observability tooling that keeps pipelines trustworthy at scale
• Participate in on-call and production support, diagnosing and resolving data quality issues quickly and thoroughly
• Write and maintain clear technical documentation for the systems you build