Data Engineer

Remote - US

Full Time Senior-level / Expert USD 76K - 150K *
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LaunchDarkly

LaunchDarkly provides fast, scalable feature flag & toggle management (feature management) for the modern enterprise. Increase your deployment velocity, software reliability, and release confidence with the developer’s choice for feature...

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About the Job:

Our team is seeking a talented developer with a focus on Data Engineering to build the next generation of experimentation systems. You will help us architect and write fast, reliable, and scalable data processing tools to process data from our thousands of customers and their hundreds of millions of users around the world. We're looking for someone who knows what it takes to deliver value to customers and takes pride in the quality of their work.

Our data platform processes events from over twenty billion feature flag evaluations. The core technologies we use daily include Golang, Scala, Kinesis, and Flink. As part of our you-build-it-you-run-it culture, all developers may be responsible for supporting applications in production, including on-call.

What you'll get to do: 

  • Build, scale, and maintain our data pipeline, and experimentation solutions
  • Explore available technologies, and design solutions to continuously improve our data quality, workflow reliability, scalability
  • Champion engineering standards, tooling, and processes
  • Participate in the development of our APIs and UIs

On day one, you should have:

  • Proven experience and fluency in a JVM language or Golang
  • Experience building data platforms (e.g. using Flink, Kafka, DataFlow, Hadoop, Spark)
  • Strong communication skills, a positive attitude, and empathy
  • You write code that can be easily understood by others, with an eye towards maintainability
  • You hold yourself and others to a high bar when working with production systems
  • You value high code quality, automated testing, and other engineering best practices

Bonus Points:

  • Experience with AWS
  • Experience with experimentation systems / products
  • Working knowledge of ETL and a query language

About LaunchDarkly:

LaunchDarkly is a Feature Management Platform that serves over 20 Trillion feature flags daily to help software teams build better software, faster. Feature flagging is an industry standard methodology of wrapping a new or risky section of code or infrastructure change with a flag. Each flag can easily be turned off independent of code deployment (aka "dark launching"). LaunchDarkly has SDKs for all major web and mobile platforms. We are building a diverse team so that we can offer robust products and services. Our team culture is dynamic, friendly, and supportive. Our headquarters are in Oakland.

At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status.

Don't let the confidence gap get in the way of applying! We'd love to hear from you.

We've partnered with KeyValues to help demonstrate the amazing culture we've built here at LaunchDarkly, find more info at https://www.keyvalues.com/launchdarkly

LaunchDarkly is also committed to giving back to our community and is a part of Pledge 1%, an organization that helps companies make this a priority. Through this initiative and its charitable arm, the LaunchDarkly Foundation, the company is committed to such causes as supporting education for the underserved, homelessness relief and moving towards having a net-zero carbon footprint. You can find more about the LaunchDarkly Foundation and the organizations we serve at https://launchdarkly.com/foundation/.

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* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net
Job perks/benefits: Team events
Job regions: Remote/Anywhere North America
Job country: United States
Job stats:  2  0  0
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