Fullstack​/Backend Software Engineer

The Company

Arta is on an audacious and incredibly rewarding mission: to pave the way for people everywhere to lead more successful financial lives. Arta leverages AI and sophisticated digital tools—once reserved for ultra-high-net-worth individuals—and makes them accessible to a broader global audience. Think of it as your own digital family office, combining intelligent investment strategies, alternative assets, private market access, and smart automation to help you grow and protect your wealth effortlessly.

We value trust, teamwork, and adaptability. Think: intelligent investing, personalized portfolios, and real-time trading, all backed by robust data infrastructure.

The Engineering team at Arta is building the backbone of our mission—powering everything from ingesting data and making it accessible to our UI, research, and trading services, to managing users’ money and integrating with external fintech platforms.

At Arta, everything revolves around data: from training and deploying ML models, to managing wealth, to delivering intuitive, high-performance user interfaces. We build for scale, speed, and transparency—and we’re looking for someone who thrives at the intersection of performance engineering and fintech innovation.

This means not just ingesting and storing data efficiently, but also making it reliably available to a wide range of services, each with its own performance and access requirements. In this role, you’ll be responsible for building a core internal service that unifies diverse data sources—market data, economic indicators, and more—into a consistent, accessible model across our systems.

You’ll work with a team of product managers, designers, ML researchers, and investment professionals to ideate, prioritize, define, prototype, develop, test, and iterate on the software that will fundamentally change our users’ relationships with their money. We're looking for engineers who are versatile and enthusiastic about taking on new problems as our fast-paced business rapidly evolves.

• Designing and coding full stack, backend, or frontend features

• Collaborate in the whole life cycle of the software development – from collecting requirements and iterating on design to implementation and testing

• Design and implement scalable, secure, and high-performance backend systems to power our trading platform and data analytics infrastructure

• Own and evolve our data ingestion and processing pipelines from financial data providers, exchanges, and internal systems
  Collaborate with frontend, data science, and product teams to deliver seamless user experiences backed by real-time and historical data

• Build RESTful APIs and/or gRPC services for use by internal and external consumers
  Ensure system reliability, observability, and fault tolerance across distributed components

• Contribute to architectural decisions, especially those involving microservices, event-driven systems, and data streaming

• Partner closely with product managers, user experience designers, and other cross-functional teams

• Stay current on market data standards, trading protocols, and regulatory considerations (MiFID II, FINRA, etc.)

• 4+ years
  of backend software engineering experience in high-stakes environments

• Strong experience in Python, Go, or Java (we’re flexible, but bonus points for Python
  )

• Proven track record working with data-intensive systems (batch + real-time), especially in the fintech, trading, or market data space

• Experience building and scaling data pipelines (e.g., using Kafka, Spark, Airflow
  , or equivalent tools)
  Familiarity with market data feeds, order management systems
  , or electronic trading platforms

• Strong grasp of distributed systems
  , cloud infrastructure (GCP/AWS), and containerized environments (
  Docker/Kubernetes
  )

• Knowledge of Postgre
  
  SQL, Redis, time-series databases
  , or similar

• Comfortable working in a fast-paced, ambiguous startup environment—roll-up-your-sleeves energy is a must

• Bonus:
  Familiarity with quantitative finance, portfolio optimization, or risk modeling

• Bonus:
  Exposure to ML-driven systems for trading or investment management

• Bonus
  
  Experience with Graph
  
  QL, gRPC, or Web…