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27 Jul 2022

Full-Time Staff Data Engineer

Stash – Posted by Stash2022 United States

Job Description

Want to help everyday Americans build wealth? Financial inequality is increasing and too many people are getting left behind. At Stash, we believe in the power of simplifying investing, making it easy and affordable for everyday Americans to build wealth and achieve their financial goals.

We’re one of the fastest growing fintechs in the U.S. and have had another record-breaking year. In 2021 we almost doubled our headcount and valuation. Our personal finance app makes investing easy and affordable; this year 6 million customers set aside more than $3 billion with Stash.

Prioritizing People is one of our core values and has been key to a healthy work-life balance and a great sense of fulfillment and inclusion. We employ a true people first – hybrid model. Live and work where you feel the most productive, whether that is in our home, in an office, or a combination of both. Anywhere in the US or UK.

Let’s solve complex problems and tackle wealth inequality.

We look for people who will help raise the bar for our entire engineering organization in terms of tech prowess, passion for collaboration and desire to mentor and educate fellow team members. We look for strategic thinkers and creative problem solvers with a bias for execution and we’ll expect you to contribute code as well as product/feature ideas from the get-go.

Our team has built an amazing modern data platform and we would like to add many advancements such as real time streaming, many tools around data governance. As a Staff Data Engineer, you will be responsible for enhancing our data infrastructure to take it to the next level, in collaboration with the team members. You will also be an active contributor in the ongoing maintenance of the existing pipelines. Stash is a data-driven organization and data infrastructure is a critical part of our overall infrastructure. You will have the opportunity to make an impact in the companies’ OKRs by coordinating with data science, marketing teams and backend teams by aligning with their data needs. We work with the latest technologies in the big data space and are seeking folks who would like to do the same.

Tech stack (evolving):

Spark, Scala, Python, Kafka, AWS EMR, Hive, Redshift, Lambda, SNS, SQS, S3, Looker, DynamoDB, CircleCI, Terraform.

What you’ll do:

  • Contribute to the design/architecture new initiatives such as real time streaming pipelines, tooling around data governance, build job orchestration abstractions to manage resources on AWS
  • Collaborate with the team to build tools for data science/marketing teams
  • Design integration pipelines for new data sources and improve existing pipelines to perform efficiently at scale
  • Provide technical guidance to the team
  • Leverage best practices in continuous integration and deployment to our cloud-based infrastructure
  • Optimize data access and consumption for our business and product colleagues

Who you are:

  • 4+ years of professional experience working in data warehousing, data architecture, and/or data engineering environments, especially using spark, hadoop, hive etc with solid understanding of streaming pipelines.
  • At least 1+ years of experience in streaming pipeline development
  • Proficiency in at least one high-level programming language Scala
  • Good understanding of databases
  • BS / MS in Computer Science, Engineering, Mathematics, or a related field
  • You have built large-scale data products and understand the tradeoffs made when building these features
  • You have a deep understanding of system design, data structures, and algorithms
  • You have an excellent knowledge of distributed computing frameworks such as Hadoop MapReduce, Spark.
  • You have a strong knowledge of following AWS infrastructure – EMR, S3, Redshift
  • You have strong understanding of data quality, governance
  • You are a team player, self-driven, highly motivated individual who loves to learn new things

Gold stars:

  • Experience in Machine Learning infrastructure
  • Experience in Search Engines

*No recruiters please**

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How to Apply

Please apply here

Job Categories: Equal Opportunities. Job Types: Full-Time. Salaries: Not Disclosed.


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