The RoleThis role offers a mix of data infrastructure, distributed systems, financial data, and product engineering. You will work on systems that ingest and normalize complex financial datasets, calculate portfolio and investment metrics at scale, and turn that data into reliable products and experiences for our clients.
What You Will DoMarket Data & Core Data Infrastructure - We are expanding market-data coverage across additional global markets and expect to support increasingly rich instrument-level datasets over time. The team owns core data infrastructure responsible for mapping, cleaning, formatting, and validating data across dozens of pipelines and services.
- 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
Alternative Investments Data - We are expanding our support for alternative investment data. This work spans the full data lifecycle, from bringing new data into the platform to making it reliable and useful to end users.
- 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
Investment Performance Metrics - We operate services that calculate investment performance metrics across client portfolios. As the number of accounts and volume of data grow, we are investing in making these systems significantly more scalable and efficient.
- 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
B2B Asset Master - We are building an Asset Master to support B2B agentic workflows, with a focus on providing reliable and structured asset data to downstream workflows.
- Building and maintaining data feeds for B2B agentic workflows
- Improving data quality and reliability
- Supporting new B2B integrations and use cases as they grow
Business Intelligence & Metrics - The team owns and improves our internal business intelligence and metrics dashboards, which provide visibility into key business, product, and operational metrics which includes the following:
- 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
Who You Are- 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.
- Location: Bay Area preferred (3 days/week in our Mountain View office). We're flexible for exceptional remote candidates on the West Coast.
Interview Process- Introduction with Head of Talent, 20-30m
- Engineering Team Conversation 30m- PHONE CALL
- Coding/Algorithm/Data Structures, 60m - VIRTUAL
- Coding/Algorithm/Data Structures, 60m - ONSITE
- Domain Knowledge & System Design, 60m - ONSITE
- Co-founder Interview, 30m
Note: We require at least one in-person interview before making our offer decision. For remotely located candidates, we may request you to visit the Mountain View HQ to meet the team.Interview Integrity NoticeTo ensure a fair and accurate assessment, candidates are expected to complete all interview exercises independently, without the use of external assistance or AI tools. Arta may, with your consent, request that you share your full screen during technical portions of the interview to verify your work environment. Interviewers may also, with your consent, ask you to temporarily disable virtual backgrounds or filters to confirm your identity and maintain interview integrity. These steps are voluntary, used only for real-time verification, and do not involve recording, storing, or accessing any information beyond what you choose to display during the session.What We Offer- A competitive salary and benefits package, with ample opportunities for growth and advancement
- A vibrant and dynamic work environment where innovation, collaboration, and continuous learning are highly valued
- The opportunity to work with a diverse and talented team of industry experts, passionate about shaping the future of finance
- Robust health insurance offering for you and your family
- High deductible health plan available with health savings account contribution
- Generous parental leave
- Competitive PTO benefits
Arta's Compensation PhilosophyWe determine your salary based on factors including your interview performance, job-related skills, experience, and relevant education or training. Our offers are based on salary bands that are updated periodically using market benchmarks and consider geographic location as well (for example, higher cost regions like San Francisco or New York). If you are presented with an offer, we will review the base salary, benefits, number of options, notional option value and strike price. We would like to know if you accept our offer within 7 days.
Please keep in mind that the equity portion of your offer is not included in these numbers and represents a significant part of your total compensation.
IC I: 110,000-180,000
IC II: 160,000-230,000
IC III: 180,000-300,000
