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Applied Systems

Sr. Data Engineer

Posted 5 Hours Ago
Remote or Hybrid
Hiring Remotely in United States
70K-150K
Senior level
Remote or Hybrid
Hiring Remotely in United States
70K-150K
Senior level
As a Senior Data Engineer, you'll design and maintain scalable data pipelines, optimize data storage, and support AI initiatives in the insurance domain.
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Job Description
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 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, and Software Engineers to build, model, and maintain data solutions as we optimize data architecture and accessibility of large-scale datasets for our global teams.
What You'll Do
  • Design and maintain scalable data pipelines that support downstream AI/ML/LLM workflows including 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 big data technologies
  • Implement scalable and efficient data solutions
  • Stay current with industry trends and advancements in data engineering and data technologies

We're Excited to Learn More About You
We're looking for someone who:
  • Can work remotely or from an Applied office

Your experience should include some or all of the following:
  • Advanced understanding and practice of 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
  • 7+ years of cloud-based high-level experience focused on modeling, building, and maintaining data solutions
  • Own working with Infrastructure-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
  • Strong understanding and advanced knowledge of data modeling, data warehousing concepts, and big data architectures
  • Experience managing and optimizing Google Cloud Platform data services
  • Knowledge of Agile frameworks, ideally Scrum, and tools like Jira and Confluence
  • Ability to communicate with global team members in a team-oriented environment to clarify requirements, confirm priorities, and deliver solutions within committed timelines
  • Advanced analytical and problem-solving skills, with a detail-oriented mindset
  • Bachelor-level degree in Computer Science, MIS, or CIS, or equivalent experience
    • We proudly support and encourage people with military experience, as well as military spouses, to apply

When You Join Team Applied, You Can Expect:
A culture that values who you are and recognizes that you aren't just an employee; you are a teammate, and you matter. We thrive on the benefits of our different experiences and celebrate the uniqueness our teammates bring to work with them every day.
We flex our time together , collaborating remotely and in-person to empower our teams to work in the ways that work best for them.
A comprehensive benefits and compensation package that centers our teammates and helps them to bring their best to work every day:
  • Medical, Dental, and Vision Coverage
  • Holiday and Vacation Time
  • Health & Wellness Days
  • A Bonus Day for Your Birthday

Learn more about the people behind our products at https://www1.appliedsystems.com/en-us/about-us/jobs/
Your Security Matters:
Our candidates' personal information and online safety are top of mind for us. At Applied, we proactively protect your personal information and only communicate with candidates via a secure @appliedsystems.com email or through our official careers portal. Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers.
EEO Statement
Applied Systems is proud to be an Equal Employment Opportunity Employer. Diversity and Inclusion is a business imperative and is a part of building our brand and reputation. At Applied, we don't discriminate, and we are committed to recruit, develop, retain , and promote regardless of race, religion, color, national origin, sexual orientation, gender identity, disability, age, veteran status, and other protected status as required by applicable law.
#LI-Remote

Top Skills

BigQuery
Google Cloud Platform
Object Storage
Pub/Sub
Python
Scala
Spark
SQL

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