DataOps Engineer
At Retina, we enable businesses to tell data stories about their customers. We use data science to predict future buying behavior of consumers and recommend actions that businesses can take around those predictions. Our founding team has led data science teams at Facebook and Paypal, built and sold companies, and built the core tech behind several startups. We are venture-funded and looking for the next few passionate team members who want the opportunity to transform the world. Apply Here
Overview:
As a DataOps Engineer, you will be working closely with the Chief Technology Officer to leverage the best technologies and techniques to build out dataops at Retina. That is to automate fast, available, and accurate data to super-charge the data science we deliver to our clients. The perfect candidate will love automating via code, be comfortable with AWS services, and have had experience with Big Data systems such as Apache Spark. We look for self-starters focused on results, who have a proven track record of success with multiple technologies and data sets. Data is at the core of what we do at Retina; and this position is an opportunity to build and innovate the way we do date.Responsibilities:
- Own the data lifecycle. From ingest and automated quality checks, to discovery and usage.
- Automate and enhance data and machine learning pipelines in Databricks using Spark / Python (PySpark)
- Empower Retina team members with fast self-service access to data for ad-hoc analysis
- Advise and assist our clients in integrating with Retina
- Innovate on bringing the best technologies and tools to empower data at Retina
Qualifications:
- 1-2 years experience with analytics, databases, and data systems
- Bachelors in Engineering, Computer Science, or related technical degree
- Strong proficiency in SQL, Python, and AWS
- Experience with large relational data in various formats
- Experience in at least one big data relational database technology such as Snowflake, Cassandra, Redshift, BigQuery