Data Engineer

NEXT’s mission is to help entrepreneurs thrive. We’re doing that by building the only technology-led, full-stack provider of small business insurance in the industry, taking on the entire value chain and transforming the customer experience.

Simply put, wherever you find small businesses, you’ll find NEXT.

Since 2016, we’ve helped hundreds of thousands of small business customers across the United States get fast, customized and affordable coverage. We’re backed by industry leaders in insurance and tech, and we still have room to grow — that’s where you come in.

We are looking for a talented data engineer to join our team.

The mission of our group is to build a trusted, easy to use and agile Data Platform, that empowers data consumers to make good decisions and accomplish business goals

• Our stack lives on AWS and includes Redshift, Spark, Kinesis, Athena, Tableau, Apache Airflow, and Neo4J.
• We are always exploring new tools and technologies and we're looking for our NEXT team member!

What You’ll Do:

• Design and develop scalable data processes, data models, and data pipelines using advanced technologies
• Ensure data accuracy, quality, and completeness through data quality tests
• Optimize data systems for performance, scalability, and cost-effectiveness
• Collaborate with peer engineering teams (backend & frontend developers and architects) as well as data scientists, product managers, and data analysts
• Be a Go to Person - a technological focal point that will guide, mentor, and share knowledge with all the data engineers group.

What We Need:

• At least 3-4 years of experience as a Data Engineer or equivalent experience in data processing and data modeling development
• Relevant academic degree - computer science/information systems or equivalent experience
• Excellent knowledge of SQL with a good technical understanding of how things work under the hood
• Programming skills: Preference for Python. Alternatively, java, C#, or other common OO languages
• Experience in Data Modeling
• Experience with technologies and tools including:
• Columnar, distributed databases: Preference for Redshift. Alternatively, Bigquery, Vertica, Snowflake, etc.
• Relational databases: Preference for MySQL. Alternatively, AWS-Aurora, SQL Server, PostgreSQL, Oracle, etc.
• Streaming data technologies: Preference for Kinesis
• Data processing and storage technologies: AWS Athena, Spark Presto, Hive, Hadoop -an advantage
• Orchestration tools (Airflow, Jenkins, etc.) -an advantage
• Cloud data services: Preference for AWS-an advantage
• A proactive approach with a self-starter attitude - knows how to promote initiatives and check new tools and technologies
• Excellent problem-solving, analytical, and communication skills