As a Data Engineer at Coda, you'll be part of a fast-growing startup, and will be responsible for building data pipelines, warehousing infrastructure, user profile service, experimental infrastructure, and otherwise enable our analytical capabilities. Your work will unlock insights enabling our team to execute with speed and confidence. Your systems, like the user profile service, allow us to tailor the product experience based on our customers' needs and behaviors. With your background in data processing, warehousing and ML you'll partner with our existing Data Science team to evolve the data processing and experimentation platform that drives our business insights. If you are data curious, excited about designing data systems and tools that have tangible impacts on our business and product, we'd love to hear from you!
You will report to our Growth Engineering Manager.
Key responsibilities include
- Building, migrating, and maintaining robust ETL pipelines from different sources (S3, Relational Databases) to Snowflake with Apache Airflow
- Optimizing the performance of business-critical queries and dealing with ETL job-related issues including tuning application and query performance
- Gathering and understanding internal data requirements, working in the team to achieve high-quality data ingestion and build systems that can process the data and transform the data, providing ad-hoc access to large data-sets
- Development of our experimentation infrastructure used for A/B testing
- Support and development of our user profile service
Skills and Experience
- Bachelor's degree or equivalent experience in a technical focused discipline such as computer science, engineering or math
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- 3+ years of experience with data warehousing systems such as Oracle, Redshift, Teradata, SQL Server, etc.
- Experience in configuring and deploying into AWS (or other public clouds)
- Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
This role can work from San Francisco, Mountain View, or Bellevue.
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