Software Engineer, Data Infrastructure and Performance Metrics

Arta Finance leverages AI and digital tools to make sophisticated financial products more accessible to a broader audience. The Software Engineer will build and improve data infrastructure, distributed systems, financial data pipelines, investment performance services, B2B asset data feeds, and business intelligence tools.

Responsibilities:

• Expand global market and instrument data coverage
• Build and improve reusable data-processing infrastructure
• Strengthen data quality and validation systems
• Improve the reliability and maintainability of a large collection of production data pipelines
• Establish better patterns for shared ownership and operational resilience
• Backend data ingestion, validation, and integration with downstream systems
• Frontend experiences for displaying investment data
• Internal tooling for identifying, validating, and correcting data issues
• Tools and workflows for onboarding new accounts and funds
• Ongoing improvements as we support more accounts, funds, and data sources
• Improving how large volumes of portfolio data are read and processed
• Optimizing performance calculations and reducing processing time
• Evaluating distributed data-processing approaches for computationally intensive workloads
• Simplifying existing calculation pipelines as we integrate additional external data sources
• Improving the reliability, observability, and maintainability of performance systems
• Building and maintaining data feeds for B2B agentic workflows
• Improving data quality and reliability
• Supporting new B2B integrations and use cases as they grow
• Maintaining and improving BI dashboards and reporting
• Building new metrics and views as business needs evolve
• Ensuring the underlying data is accurate, reliable, and easy to understand
• Improving the overall self-service analytics experience across the company

Requirements:

• 3+ years experience in software engineering with a primary focus on the reliability, observability, and maintainability of production-grade systems
• Proven experience building and maintaining scalable data infrastructure, including end-to-end ingestion, validation, and integration pipelines for complex datasets
• Proficiency in optimizing data-processing workflows and calculation performance to handle high-volume portfolio data efficiently and reliably
• Demonstrated ability to develop internal tools and dashboards that improve data quality, business intelligence, and self-service analytics capabilities
• Strong capacity to design and implement robust, reusable data schemas and workflows that adapt to evolving product needs and B2B integrations
• A collaborative mindset that prioritizes shared ownership, operational resilience, and effective cross-functional teamwork
• Hands-on experience with distributed data-processing approaches and managing computationally intensive workloads
• Experience with Financial dataset is a plus
• Bay Area preferred