Staff Data Engineer
San Francisco, CA
Engineering – Engineering
As Staff Data Engineer you will own our entire data and analytics platform. Plastiq is a data-driven organization - data is at the core of our business, providing insights into the effectiveness of our teams and our products, driving our decision-making as a company. You will be a key contributor on our data engineering team and help build, optimize and evolve it to support our growth. You will be a Data Guru of Plastiq. You get to work with a fun, supportive, and high energy team that takes pride in building exceptional software.
Our Data Stack
At Plastiq we have incrementally built our current internal data and analytics platform (as a startup we had to be scrappy) - we have MySQL databases for our production OLTP systems, a partially de-normalized MySQL database fed via ETL process for Risk/Compliance and an AWS RedShift database fed via Fivetran that serves as our data warehouse. Our teams use a number of tools (Mode Analytics, Periscope) to generate reporting off of these data stores.
We are making a substantial investment in our data stack and building out new pipelines and platform to support our thirst for data and analytics as our company grows. You will help us build out this new platform that takes our data and analytics platform to the next level. This role will work closely with our rapidly-expanding Data Science team, the key users of this platform.
- Design and deliver data infrastructure and systems to scale easily as data grows.
- Design, develop, and implement optimal and secure data pipeline at scale sourced from a wide variety of data sources.
- Perform database management and optimization for our MySQL and Redshift/Snowflake Databases.
- Implement comprehensive unit-tests and production monitoring to verify high quality and detect data quality issues quickly.
- Be self-driven, understand the data we have and its scale, and provide data solutions to all of our challenges.
- 7+ years of hands-on technical experience in a data engineer role.
- Advanced working SQL knowledge and experience is required, No-SQL experience is a plus.
- Experience building pipelines in Python is required. Spark experience is a plus.
- Experience with Python data processing libraries such as Pandas, Numpy is required.
- Experience with frameworks such as Flask, Django is a plus.
- Experience with ML libraries such as scikit-learn, TensorFlow, Scrapy is a plus.
- Experience in data technologies such as AWS RDS (Aurora/MySQL), No-SQL databases (MongoDB, DynamoDB etc) etc.
- Experience with modern MPP systems such as Snowflake or Redshift.
- Solid experience building and optimizing data pipelines, architectures, and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with modern BI tools (Periscope, Looker, Tableau, Superset etc.).
- Experience with the AWS Ecosystem, especially Kinesis, ECS, EMR and Lambda.
- Knowledge and experience working with Docker containers.
- Experience with stream processing technologies such as Kinesis stream, and/or Kafka Streams.
A little bit about us
To learn more about our team and how we operate, see our Engineering Blog. To learn more about our culture, visit https://www.keyvalues.com/plastiq.
At Plastiq, we’re committed to helping small businesses achieve their growth potential. The opportunity is huge, and the need is very real. With over 1 million customers and hundreds of thousands of vendors paid, we’re in a phenomenal position to make that happen. Most importantly, we have the team, the technology and capital to make our vision a reality. By accelerating our own growth potential, we will do so for small business owners as well.
Plastiq is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.