Altruist · Posted 1d ago
Staff Back End Engineer (Data)
Job relayed by Stapply Data, its source: you apply there.
- Location
- 🇺🇸 San Francisco, United States
- Contract
- Full-time
- Role
- Data engineering
- Source
- Stapply Data
The posting
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 also establish standards for data quality, observability, and recovery, and mentor engineers to raise engineering standards. Enjoy competitive compensation, health benefits, and a commitment to inclusivity.
- Set technical direction for scalable data pipelines and data serving platforms, aligning architecture and investment decisions with business priorities. - Design and build high-performance systems that manage the full lifecycle of financial data, from ingestion and transformation to serving and consumption. - Lead initiatives spanning multiple teams, clarify technical tradeoffs and dependencies, and guide delivery from initial design through rollout and ongoing operation.
- 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 - Experience - 8+ years of software engineering experience, with a track record of leading complex platform or distributed systems initiatives and delivering results across teams - Ownership - You take responsibility for business outcomes, carry changes through production, and support the systems you build - Distributed processing - Experience with large-scale offline processing and batch pipelines using Spark or similar frameworks, including failure recovery and performance tuning - 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 - Communication - You listen carefully, explain complex ideas clearly, and work effectively with technical and nontechnical partners - Technical leadership - Experience setting architectural direction, writing clear technical proposals, building alignment across teams, and mentoring engineers without relying on formal authority - Creative problem solving - You question assumptions, identify root causes, and develop practical solutions to difficult problems - Cloud infrastructure - Experience designing and operating cloud services, especially on AWS, with working knowledge of Kubernetes, deployment practices, and observability - Education - B.A. or B.S. in Computer Science, or equivalent practical experience - 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 - Hands-on engineering - Strong proficiency in Python or Java, strong SQL skills, and the ability to design, build, debug, and operate production systems - Snowflake, Airflow, or dbt in production environments - 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