Data Engineer / Senior Data Engineer (GCP / AI)

Job Overview

Amazing Career Moments Happen Here  

Transforming the insurance industry is ambitious, we know. That’s why at Applied, we’re building a team that shows up every day ready to learn, willing to try new things, and driven to deliver innovative software and services that make us indispensable to our customers – all within a culture built on values that make us indispensable to each other too. With 40+ years of experience in the insurtech game, we’re not just redefining what’s achievable, we’re creating a place where amazing career moments are made possible.  

  

Position Overview  

We're seeking a Data Engineer / Senior Data Engineer to build and enhance data solutions and AI initiatives for the business of insurance. In this role, you will work closely with the Principal Data Engineer, Data Scientists, Software Engineers, and Product to contribute  by building, maintaining and optimizing data solutions, data architecture, and software architecture.  

 

What You’ll Do

• Our AI Engineering Team is looking for a Data Engineer who will:  

  • Implement and maintain scalable data pipelines to support downstream AI/ML/LLM workflows including but not limited to data labeling, classification, and document parsing 
  • Work with Data Scientists and Data Labeling teams to ensure reliable access to structured and unstructured data sources used in AI/ML and LLM workflows 
  • Manage and optimize data storage, partitioning, and clustering strategies to ensure high performance and reliability of our data infrastructure 
  • Develop and implement features and enhancements leveraging your SQL and ETL expertise, and cloud-based data warehousing technologies 
  • Collaborate with cross-functional teams to understand AI data requirements and deliver solutions aligned with business objectives, security requirements, and guidelines for data governance 
  • Develop documentation for the team to support design discussions 
  • Ensure data integrity and quality by implementing robust data validation and error-handling mechanisms to prevent data corruption. Maintain and advocate for these standards through code review. 
  • Identify and implement improvements across the full lifecycle of data management, including data expiry layers, from ingestion to ETL processes to increase productivity on the team 
  • Continuously build knowledge of industry trends and advancements in data engineering and robust data technologies 
  • Implement scalable and efficient data solutions 
  • Stay current with industry trends and advancements in data engineering and data technologies 

   

• Senior Data Engineer level team members would additionally be able to:  

  • Support delivery by sharing comprehensive feedback and guidance with the team to address complex technical problems 
  • Assess the opportunities and risks of various solutions to provide insights and input into technical decisions as we continuously build for scalability and security while maintaining high velocity  
  • Share advanced knowledge of AI/ML and LLM workflows based on prior experience building data infrastructure and managing structured and unstructured data  
  • Support continuous improvement of internal processes and documentation to champion a principles-based approach to design, implementation, and testing.   

 

We’re Excited to Learn More About You  

We’re looking for someone who:

• Can work remotely or from an Applied office

• The position could be an excellent match for a Data Engineer with:  

  • Practical experience supporting AI/ML and LLM workflows by building data infrastructure, managing unstructured data, and orchestrating secure, cloud-based data pipelines using CI/CD and workflow automation practices 
  • 4+ years of cloud-based experience focused on data modeling, building, and maintaining data solutions 
  • Experience working with Instructure-as-Code (IaC) and cloud native data solutions, such as BigQuery, Spark, Pub/Sub, and Object Storage 
  • Proficiency in SQL and developing high-level code with languages such as Python or Scala to manipulate, store, manage, or retrieve data assets 
  • Knowledge of data modeling, data warehousing concepts, and data architecture 
  • Communication experience with global team members to confirm requirements, priorities, and plans for delivery within committed timelines 
  • Bachelors or Masters degree in Computer Science, MIS, or CIS, or equivalent experience 
  <