Senior Data Engineer [Remote-US]

Quanata is on a mission to help ensure a better world through context-based insurance solutions. They are seeking a Senior Data Engineer to help deliver data science services and build data pipelines that integrate data from multiple sources for risk evaluation and business intelligence.

Responsibilities:

• Design and build robust data pipelines that integrate data from diverse sources to support risk evaluation and business intelligence
• Build streaming data pipelines using Kafka and AWS services to enable real-time data processing and decision-making
• Create and operate data services that make curated datasets accessible to internal teams and external partners through APIs and scheduled deliveries
• Support data science workflows by building infrastructure that enables model training, feature engineering, and production inference
• Implement data quality frameworks including validation, monitoring, and alerting to maintain trust in our data assets
• Contribute to CI/CD pipelines and infrastructure-as-code practices to ensure reliable, repeatable deployments
• Deliver highly reliable services by following engineering best practices and participating in an on-call rotation to support production systems
• Contribute to the data warehouse by creating well-modeled datasets in Snowflake that empower analysts and data scientists
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions that drive value

Requirements:

• Bachelor's degree or equivalent relevant experience
• 6-8 years of industry experience in data engineering or software engineering with a focus on data systems
• Strong proficiency in Python and SQL for data pipeline development and analysis
• Experience with AWS data platforms (Glue, S3, Athena, Lambda, Step Functions)
• Familiarity with Snowflake or similar cloud data platforms
• Familiarity with streaming technologies such as Kafka or Kinesis
• Experience with workflow orchestration tools (Airflow, Step Functions, or similar)
• Proficiency in infrastructure-as-code tools like Terraform
• Understanding of data modeling principles
• Excellent written and verbal communication with a strong collaborative focus
• Experience with CI/CD tailored for machine learning systems (e.g., automating model training, validation, and deployment)
• Prior experience working within the insurance industry or another highly regulated environment, demonstrating an understanding of pertinent regulatory, security, and data governance challenges
• Familiarity with ML infrastructure and supporting data science teams in productionizing models
• Experience designing and building feature stores or real-time feature serving systems
• Exposure to data governance and cataloging tools (e.g., DataHub, Atlan, or similar)