Fig is building a digital food-as-medicine platform to help anyone with complex dietary needs live an easier, healthier life around food. We're a fast-growing, early-stage startup supporting over 1,000,000+ users and backed by top VCs including Sequoia, Artis Ventures, Goodwater Capital, and Correlation Ventures. Our users love us (4.7 stars on app stores) as Fig changes their lives: "THANK YOU!! It is sometimes such a struggle to find PCOS-compliant snacks, ingredients, etc. This app has truly changed my life in the 2 weeks I’ve had it!”

Fig’s mission is to help millions of people with dietary restrictions more easily find food. Our core product, the Fig phone app, already helps hundreds of thousands of people navigate food at grocery stores and restaurants each month.

Our company is seeking a highly skilled Data Engineer with extensive experience in building data ingestion, processing, and instrumentation systems at scale.

What You will do:

As a Data Engineer at Fig, you will:

  1. Design, develop, and maintain our data architecture, data models, ETL pipelines, and data warehouse.
  2. Collaborate with cross-functional teams to identify business needs and translate them into data solutions.
  3. Implement and optimize data ingestion processes from multiple data sources for real-time analytics and business intelligence.
  4. Set up orchestration engines to run data ingestion processes in the cloud.
  5. Monitor, troubleshoot, and optimize the performance of data pipelines and database systems.
  6. Assist in developing data governance and data quality processes and ensure compliance with data privacy and security policies.
  7. Stay up-to-date with the latest technologies and trends in the data engineering field.

Qualifications

Who you are:

  1. At least 3-5 years of professional experience in data engineering or related roles.
  2. Proficiency in SQL and Python and experience with ETL tools such as FiveTran, DBT.
  3. Experience with cloud platforms (AWS, GCP) and cloud data platforms (Snowflake/Databricks)
  4. Solid understanding of database design, data warehousing concepts, and data modeling.
  5. Proven ability to build and maintain data pipelines and deliver high-quality data solutions.
  6. Strong problem-solving skills, analytical capabilities, and attention to detail.