Software Engineer, Data

About Found

Found is revolutionizing the way self-employed individuals manage their finances by providing innovative tools that offer security and peace of mind traditionally reserved for large corporations. As a business bank account designed specifically for small business owners and freelancers, Found automates essential financial tasks such as taxes and expense tracking, enabling entrepreneurs to focus more on their core passions and less on administrative burdens. Our mission is to create a safety net for self-employment, empowering individuals to thrive without the complexities typically associated with financial management.

Our dedicated Data team is a full-stack data organization comprising highly skilled data scientists, data engineers, and machine learning engineers. We handle a broad spectrum of responsibilities, from researching, training, and deploying machine learning models to detect and prevent fraud in real-time, to leveraging data insights to guide product development and strategic decision-making. With a small but experienced team that has previously worked at renowned companies like Uber, Block (formerly Square), and Spotify, we are committed to building scalable data infrastructure, optimizing data pipelines, and establishing robust data governance practices to support our organizational growth.

Recent accomplishments include deploying a new feature store that reduced ML model training and deployment times by approximately 50%, optimizing batch and streaming jobs to cut reporting latencies from days to hours, and deploying real-time transaction monitoring models to enhance financial security. Our team also prioritizes data governance, ensuring clear ownership and SLAs for data assets, which supports reliable and efficient data operations across the company.

About The Role

We are seeking a talented and experienced Software Engineer, Data to join our growing team. In this role, you will be instrumental in designing, building, and maintaining large-scale data infrastructure systems across multiple environments. Your work will enable the storage, aggregation, and processing of vast amounts of data to support analytics, machine learning, and product development efforts. You will develop a data platform-as-a-service for internal stakeholders, ensuring data integrity, discoverability, and proper tagging to facilitate seamless data access.

As a bridge between engineering and analytics teams, you will help shape the company's data infrastructure roadmap, implement ETL processes for key metrics, and uphold high standards for data quality and governance. Your contributions will directly impact the efficiency and effectiveness of data-driven decision-making, empowering data scientists, analysts, and product teams to leverage data more effectively to propel the business forward.

Qualifications

• 5+ years of experience in data infrastructure, data engineering, or analytics engineering roles
• Proficiency with relational databases such as Postgres and MySQL
• Experience with data transformation and modeling tools like dbt
• Hands-on experience with workflow orchestration tools such as Airflow
• Familiarity with cloud-native big data infrastructure, particularly on Google Cloud Platform (BigQuery, Vertex)
• Ability to design effective data models for data warehouses and machine learning applications
• Experience managing and maintaining data warehouses with contributions from multiple teams, utilizing tools like Data Hub and DBT
• Strong understanding of data governance, SLAs, and metadata management
• Excellent problem-solving skills and the ability to prioritize autonomously
• Demonstrated ability to advocate for and implement new technologies and open-source frameworks

Preferred but not mandatory qualifications include prior experience in fintech, startup environments, knowledge of bookkeeping or taxes related to self-employment, and experience with feature stores such as Chalk.

Responsibilities

• Design, build, and operate scalable data infrastructure systems across multiple environments to support organizational needs
• Develop and maintain a robust data platform-as-a-service for internal teams, ensuring data quality, discoverability, and proper tagging
• Bridge engineering and analytics teams by providing reliable data pipelines and infrastructure to inform product and business decisions
• Implement ETL processes for key metrics, reporting, and product functionalities to ensure accuracy and timeliness
• Establish and enforce standards and best practices for data warehouse maintenance and governance
• Optimize batch and streaming data jobs to improve reporting latency and system performance
• Collaborate with cross-functional teams to understand data needs and translate them into scalable solutions
• Monitor, troubleshoot, and improve existing data pipelines and infrastructure components
• Stay abreast of emerging data engineering technologies and recommend improvements to the data stack

Benefits

• Competitive salary range of $181,000-$241,000, commensurate with experience and skills
• Comprehensive health, dental, and vision insurance, with coverage fully paid for employees and substantial coverage for dependents
• 401(k) plan, FSA, and commuter benefits to support financial and daily commuting needs
• Paid parental leave of 16 weeks to support new parents
• Flexible work arrangements, including fully remote options for team members outside of San Francisco and New York City
• Meaningful equity participation to foster a sense of ownership and shared success
• Generous vacation policy, encouraging work-life balance and mental health
• Access to ongoing professional development and learning opportunities

Key skills/competency

• Data Engineering
• Data Infrastructure
• ETL Processes
• Data Governance
• SQL
• BigQuery
• Airflow
• dbt
• Machine Learning Data
• Data Modeling