Mulberry is a technology company redefining how insurance is offered at the point of sale. We optimize for the consumer and for the retailer -- for ease-of-use and for scalability. We are hiring a Senior Data Engineer to grow our insurtech platform and to help us continue to transform how insurance is priced and offered to our customers. At Mulberry you will be working with a team with a broad set of technical skills and a deep experience in building insurance and financial technology products.

We want someone who is motivated to find large-scale solutions with us. We like to spend our energy developing automation wherever possible, with a particular focus on making business processes more streamlined and efficient. We work with big data on small teams, and every contribution is critical to the success of the business.

Technologies we use at Mulberry

• Many AWS services, SQL (postgres), NoSQL (redis, mongo)
• Airflow, Docker, Kubernetes, dbt, Presto
• Python, flask, sqlalchemy
• Tensorflow, PyTorch, DVC, MLFlow, Spark

What you will do

• Design, maintain, and own Mulberry’s data infrastructure day-to-day
• Devise a strategic roadmap after assessing our current data infrastructure and business needs
• Work with technical leads at Mulberry to define and enforce a strong and overarching vision for Data (all things associated with data pipelining, ETL, etc.)
• Liaison with data consumers across the business (including, but not limited to, Product, Business Intelligence, Insurance Ops) to understand the business + their requirements
• Implement and maintain data + tech workflows to ensure deliverables and enhancements are delivered in a timely manner
• Optimize processes to help move, transform and store data in large quantities and at scale
• Implement data governance strategies including setting up data quality controls and introspection structures, and monitoring data quality 
• Improve data engineering practices and documentation
• Be an active contributor and technical leader to ML + data practitioners at Mulberry
• Help develop and execute the team’s long-term strategy and roadmap

Who you are

• Passionate about machine learning and related technologies
• Have hands-on experience building and maintaining large scale ETL systems
• Deep understanding of database design and data structures
• Experience with MPP DBs such as Redshift, Teradata, and SQL + NoSQL data stores
• Have deep expertise in Python (or other general-purpose programming languages)
• Have experience with big data technologies such as Hadoop, Pig, Cassandra, Spark
• Knowledge of ETL, data curation and analytical jobs using distributed computing frameworks (Spark, Hadoop, etc.)
• Knowledge of and experience working with large enterprise-wide data warehouses
• Have 7-10 years of relevant professional experience (5 years minimum)
• Familiarity with agile software processes and care about system reliability
• Experience working with large, complex and diverse data sets from a variety of sources
• Have experience with working in a CI/CD engineering environment
• Keep up with state of the art research by reading papers, attending conferences, and participating in research communities

A plus if you have

• Experience with dbt and BI-adjacent technologies
• Scala, golang or Rust knowledge
• DevOps experience
• An MS or PhD in CS, OR, EE, Physics or related quantitative field
• Genuine interest in big data technology, incl. AI and machine learning
• Strong understanding of concurrent and parallel programming
• Experience with graph databases

The Offer

• Competitive salary
• Unlimited PTO
• Stock options
• One-time-use WFH stipend
• Full suite of benefits w/ medical, dental, vision insurance and 401(k)
• Ongoing career development with thought leaders within the company