Senior Data Engineer

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We exist to accelerate innovation. We do this by giving more people the opportunity to participate in the venture economy by building the financial infrastructure that makes it possible for more people to invest in world-changing startups. We also build tools for startup founders that help them run their operations, so they can focus on building their company.

Angel List is the nexus of venture capital and the startup community. We support over $171B+ assets on our platform, and we’ve driven capital to over 13,000 startups. 57% of top‑tier U.S. VC deals involve investors on Angel List.

While our scale is large, our ambitions are even larger – we’re innovating on the infrastructure for venture and individual investors and the startups they invest in. Come build with us!

Angel List is hiring a Senior Data Engineer who is passionate about using their technical skills to democratize data, metrics, and insights for the team. Reporting to the Head of Data, you will play a pivotal role in designing, building, and maintaining scalable data pipelines – ensuring efficient data flow and integration to support analytical and operational efficiency. With a highly skilled and experienced Data Engineer, we can accelerate the development of reliable pipelines, improve data availability, and empower faster decision‑making across teams!

If you're enthusiastic about working in a startup environment with large datasets, optimizing data systems, and enabling data-driven decision-making, we’d love to hear from you.

• Design, build, and maintain robust, scalable, and efficient ETL/ELT pipelines for structured and unstructured data.
• Implement best practices for data ingestion, transformation, and integration across multiple sources.
• Optimize and maintain data storage solutions (e.g. SQL/No
  
  SQL databases, data lakes, warehouses) for performance and cost‑effectiveness.
• Collaborate with data analysts and business stakeholders to understand data requirements and deliver solutions that meet their needs.
• Contribute to the development and implementation of the organization’s data architecture and strategy.
• Continuously evaluate and integrate new technologies and tools for automated data quality validation and to improve data engineering processes overall.
• Maintain and improve robust monitoring and alerting mechanisms for data pipelines and systems.

• 5+ years of experience designing and implementing scalable data pipelines and infrastructure.
• Strong technical expertise in modern tools and frameworks, including cloud platforms (we're built on AWS), distributed systems, and advanced SQL.
• Proficiency in programming languages (such as Ruby or Python) – you don't need to be a software engineer, but should understand our codebase.
• Hands‑on experience with data warehousing solutions like Snowflake or Redshift and orchestration tools like Airflow or dbt. (We're migrating from Redshift to Snowflake.)
• A strong sense of ownership and accountability, with a track record of proactively improving systems for performance, reliability, and cost while addressing complex technical challenges.
• Excels at cross‑functional collaboration, aligning technical solutions with business goals and delivering measurable improvements to data workflows and decision‑making.
• Curiosity and a growth mindset, demonstrated through learning new tools, deepening technical expertise, and continuously improving processes.
• Startup/high‑growth experience with the scrappiness required to be successful at Angel List!

• Delivery of reliable, scalable, and efficient data pipelines within agreed timelines, with minimal downtime and robust monitoring systems in place.
• Successful collaboration with analysts and stakeholders to enable seamless access to accurate and timely data for decision‑making.
• Tangible improvements in infrastructure scalability, cost‑effectiveness, and adaptability to evolving business needs.

If you don’t tick every box above, we’d still encourage you to apply. We’re building a diverse team whose skills balance and complement one…