Data Engineer

Qapital is looking for a Data Engineer to join the Qrew. This is a chance to work on a product that has already helped users save nearly $3 billion towards their financial goals! You’ll join the data team during an important upscaling phase, and in this role, collaborate with other team members as well as our cross-functional development teams. As a Data Engineer at Qapital, you get the best of both worlds - you get to work with big and complex data, but in the quick and agile environment of a startup!

About the Role

As a Data Engineer, you will be a part of creating a unique data infrastructure, running tests on their designs to isolate errors, and updating systems to accommodate changes in company needs. You will also play an important role in creating the data infrastructure for new exciting products that will set Qapital apart from its competitors. The data team is distributed throughout the United States and Sweden, so as a new team member, you can be based in either of those countries.



What you will do

- Create and maintain optimal data pipeline architecture.

- Assemble large, complex data sets that meet functional/non-functional business requirements.

- Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability.

- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS “big data” technologies.

- Build analytics tools that use the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

- Create data tools for analytics and data scientist team members to help them build and optimize our product into an innovative industry leader.

- Work with data and analytics experts to strive for greater functionality in our data systems.

- Build processes that supportdata transformation, data structures, metadata, dependency, and workload management.





What we look for in you

- At least 1 year of experience as a Data Engineer

- Experience with big data tools, like Spark or Kafka

- Experience with relational SQL and NoSQL databases.

- Experience with data pipeline and workflow management tools, like Azkaban, Luigi, or Airflow.

- Experience with AWS cloud services: EMR, Sagemaker, Redshift, S3, Glue, Kinesis, and Lambda for serverless ETL.

- Experience with stream-processing systems, like Storm or Spark-Streaming.

- Experience with object-oriented/object function scripting languages, like Python, Java, C++, and Scala.

- Strong analytic skills related to working with unstructured datasets

- Working knowledge of message queuing, stream processing, and highly scalable “big data” data stores

- Experience in working with complex analytics databases
- Ability to embrace flexibility and changing business priorities, and collaborate with a global team





About Qapital

Qapital is a new kind of banking experience that empowers people to maximize their happiness by saving, spending, and investing with their goals in mind. By blending behavioral science with technology, Qapital provides people with the tools they need to make managing money easy and fun. Qapital has over 2 million users and 100K+ 5-star ratings. It’s been named “Most Innovative App of the Year” by Google and “Best App for Savings” by Apple.


Application
No need to attach a CV or a cover letter. We'll let you answer a few questions and attach a link to your LinkedIn-profile instead.