Senior Data Engineer
AngelList
full-time
Posted on:
Location: California • 🇺🇸 United States
Visit company websiteSalary
💰 $190,000 per year
Job Level
Senior
Tech Stack
AirflowAmazon RedshiftAWSCloudDistributed SystemsDockerETLKubernetesNoSQLPythonRubySQL
About the role
- 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/NoSQL 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.
Requirements
- 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)
- Hands-on experience with data warehousing solutions like Redshift or Snowflake and orchestration tools like Airflow or dbt.
- Proactive problem solving with a track record of optimizing systems for performance and cost while addressing complex technical challenges.
- Excellence collaborating with cross-functional teams, aligning technical solutions with business objectives, and delivering measurable improvements to data workflows and decision-making processes.
- Startup/high-growth experience with the scrappiness required to be successful at AngelList!
- Other nice-to-have: Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.
- Other nice-to-have: Exposure to machine learning workflows and supporting MLOps tools.
- Other nice-to-have: Experience in building analytical tools or data engineering services.