Staff Back End Engineer (Data)

Join Altruist, a fast-growing company in the financial services industry, as a Staff Back End Engineer (Data). In this role, you will shape the technical direction of our data and AI platforms, lead complex initiatives across teams, and build frameworks that other engineers can use. You will own outcomes from design through production, balancing delivery speed with reliability, security, and cost. Additionally, you will establish standards for data quality, observability, and recovery, and mentor engineers to raise engineering standards.

• Concevoir et construire des systèmes performants qui gèrent l'ensemble du cycle de vie des données financières, de l'ingestion à la consommation.
• Définir la direction technique pour des pipelines de données évolutifs et des plateformes de service de données, en alignant l'architecture et les décisions d'investissement sur les priorités commerciales.
• Identifier les opportunités d'améliorer les expériences des conseillers et les flux de travail internes grâce à l'IA, en collaborant avec les équipes produit et ingénierie.

• We're looking for an AI-native Staff Software Engineer who combines creative thinking with business acumen
• Education - B.A. or B.S. in Computer Science, or equivalent practical experience
• Communication - You listen carefully, explain complex ideas clearly, and work effectively with technical and nontechnical partners
• Experience - 8+ years of software engineering experience, with a track record of leading complex platform or distributed systems initiatives and delivering results across teams
• Business judgment - The ability to turn ambiguous needs into clear priorities, make pragmatic build-versus-buy decisions, and balance immediate delivery with long-term platform needs
• Hands-on engineering - Strong proficiency in Python or Java, strong SQL skills, and the ability to design, build, debug, and operate production systems
• Distributed processing - Experience with large-scale offline processing and batch pipelines using Spark or similar frameworks, including failure recovery and performance tuning
• Creative problem solving - You question assumptions, identify root causes, and develop practical solutions to difficult problems
• AI fluency - Proficiency with AI-assisted development tools such as Cursor or Claude Code, sound judgment about their limitations, and the ability to help others use them effectively. You can identify practical applications of AI and evaluate whether they solve the business problem
• Ownership - You take responsibility for business outcomes, carry changes through production, and support the systems you build
• Cloud infrastructure - Experience designing and operating cloud services, especially on AWS, with working knowledge of Kubernetes, deployment practices, and observability
• Resilience and humility - You navigate uncertainty, learn from setbacks, and adapt your approach when evidence or a different perspective calls for it
• Data platforms - Deep experience with databases, data warehouses, ETL or ELT pipelines, and mature data processes at scale. You understand data modeling, query optimization, and the tradeoffs between batch and real-time processing
• Technical leadership - Experience setting architectural direction, writing clear technical proposals, building alignment across teams, and mentoring engineers without relying on formal authority
• Snowflake, Airflow, or dbt in production environments
• Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Altruist we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles
• Building and operating AI applications, agent frameworks, or shared services for governed data access, with evaluation and monitoring
• Financial services data or other environments where data accuracy, privacy, and reliability are essential