Software Engineer, Data

Generate • San Francisco, CA

17h • $130,000 - $160,000 • Hybrid

About The Position

Generate Capital is seeking a Software Engineer, Data to support and improve the data platform used across the firm while helping build internal software that replaces SaaS tools, spreadsheets, and manual processes. The role combines operational ownership of existing data pipelines with development of new applications and tools. The engineer will work closely with business stakeholders to understand problems, develop requirements and prototypes, and deliver working solutions. AI coding agents are expected to be a central part of the engineer’s workflow, which they will also help share across the team.

This is a hybrid role based in San Francisco, California. The estimated base salary range is $130,000–$160,000. Compensation may also include a discretionary bonus and benefits, and salary decisions depend on factors such as skills, experience, training, certifications, location, and organizational needs.

Requirements

• 2–3 years of professional software or data engineering experience; exceptional new graduates with substantial shipped work will be considered.
• Strong Python and SQL skills.
• Experience building or operating software in a cloud environment.
• Ability to explain an AI coding-agent workflow in detail.
• Comfort debugging systems the candidate did not build, under time pressure and with incomplete information.
• Ability to translate business problems into technical solutions.
• Demonstrated passion for or commitment to Generate Capital’s mission.
• Unimpeachable integrity and strong references.
• Outstanding communication and interpersonal skills, including empathy, intuition, listening, writing, and documentation.
• Self-awareness and humility, with enthusiasm for confronting uncomfortable situations and new challenges.
• Intellectual agility, curiosity, creativity, and a problem-solving orientation.
• Entrepreneurial spirit, flexibility, comfort with risk, and recognition that perfect can be the enemy of good.

Nice To Haves

• Azure cloud experience is preferred; AWS or GCP experience is also welcome.
• Experience with Snowflake and dbt.
• Experience building internal tools or full-stack applications.
• Experience in financial services, energy, or another data-heavy environment.

Responsibilities

• Own the day-to-day health of Python ETL jobs, dbt models in Snowflake, Azure Data Factory pipelines, reports, and dependent system integrations.
• Investigate pipeline failures to identify and fix root causes, including vendor schema changes, API rate limits, failed model tests, and broken dependencies.
• Work directly with business stakeholders to understand issue impacts, provide updates, and verify that resolutions address their needs.
• Collaborate with the data team on fixes, code reviews, and releases.
• Prevent recurring failures by adding alerting, validation, retries, and schema-change handling.
• Proactively identify and address weaknesses in processes, architecture, code quality, and security.
• Help define and enforce repeatable standards for deployment, logging, testing, and secrets handling.
• Build, ship, and operate internal applications that replace SaaS vendors, spreadsheets, and manual processes.
• Translate stakeholder problems into requirements, prototypes, and working software.
• Use AI coding agents as a default part of the workflow and share workflows and tooling with the team.

Benefits

• Health care benefits
• Retirement benefits
• Paid days off, including sick leave, parental leave, and paid time off or vacation benefits
• A discretionary bonus may be included in the compensation package

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed