We're looking for a Sr. Data Engineer with extensive experience in building data pipelines, ETL scripts, and moving data to /from data warehouses in a modern cloud environment.  We are a fast-paced, rapidly growing growth data analytics consultancy helping businesses build cutting edge analytics environments.

This is an excellent opportunity to sharpen and broaden your skills. In this role you'll not only have a chance to get at the data but also be influential in what to do with the data (sales, marketing, product, ops).

What You’ll Do:

• Develop and manage custom integrations with 3rd party APIs and handle ETLs to move and transform data.
• Build end-to-end data pipelines that are fault-tolerant, observable, and scalable, using advanced serverless technologies.
• Collaborate closely with our internal engineers and the client's engineers to make key business data available that will drive the client's growth.

What You’ll Need:

• Minimum of 5 years of experience as a Data Engineer, deploying high-quality production code at scale.
• A strong focus on code quality. You write code that is readable, extensible, and testable.
• Experience with various testing methodologies including unit testing and integration testing.
• Proficient in Python programming.
• Hands-on experience with AWS (Lambda, SQS, StepFunctions) or equivalent platforms in a serverless data stack.
• Extensive experience with DevOps practices, including deployment using tools like Github Actions.
• Proven ability in conducting code reviews, both submitting your own code for review and reviewing others' work.
• Experience working with cloud data warehouses for data loading tasks, such as Snowflake or Bigquery.
• Proven knowledge of APIs & Webhooks, OAuth/Tokens, and handling rate limits.

Nice to Haves:

• Excellent SQL skills
• Experience in the Modern Data Stack including tools such as Fivetran, dbt, Hightouch, etc
• Previous professional services or consulting experience
• Experience working with streaming data, message queues, and Spark