Senior Data Engineer [Remote-US]

2 months, 1 week ago
Full-time
Senior
Software Development
Quanata

Quanata

Quanata is a software development company based in San Francisco, specializing in context-based insurance solutions. The company leverages AI, real-time telematics, and data science to enhance risk prediction, promote safer driving behaviors, and create modern insurance products. Quanata aims to transform the insurance industry by fostering positive behaviors and advancing digital experiences. The company develops a range of software platforms and tools for insurers. Their offerings include AI-powered risk assessment, telematics for driver monitoring, and claims solutions that optimize and automate processes. Quanata also focuses on customer engagement through personalized products and retention tools, supporting insurtech modernization with big data analytics and cloud-native platforms. With a team of around 26 professionals, Quanata draws on talent from Silicon Valley to drive innovation in the insurance sector.

information technology & services
201-500

Description

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

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, including Glue, S3, Athena, Lambda, and Step Functions.
  • Familiarity with Snowflake or similar cloud data platforms.
  • Familiarity with streaming technologies such as Kafka or Kinesis.
  • Experience with workflow orchestration tools such as Airflow or Step Functions.
  • Proficiency with 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 for machine learning systems, including automating model training, validation, and deployment.
  • Prior experience in the insurance industry or another highly regulated environment is a plus.
  • Familiarity with ML infrastructure and supporting data science teams in productionizing models is a plus.
  • Experience designing feature stores or real-time feature serving systems is a plus.
  • Exposure to data governance and cataloging tools such as DataHub or Atlan is a plus.

Benefits

  • Salary range of $215,000 to $300,000.
  • Comprehensive health benefits including medical, dental, vision, life insurance, and supplemental income plans.
  • 401(k) plan with company match.
  • Headspace app subscription and monthly wellness allowance.
  • One-time $2,000 home office equipment stipend for remote work.
  • Four weeks of PTO in the first year.
  • Twelve weeks of fully paid parental leave for new parents.
  • Up to $5,000 per year for professional learning, continuing education, and career development, plus LinkedIn Learning and BetterUp coaching.

Interested in this position?

Apply directly on the company website

Apply Now

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