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Analytics Engineer, Senior Associate

New York Life Insurance Company LogoNew York Life Insurance Company
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Salary

Salary range: $105,000-$160,000

The Center for Data Science and Artificial Intelligence (CDSAi) is the 60-person innovative corporate Data Science group within New York Life, led by Chief Analytics Officer. We are a rapidly growing entrepreneurial department which designs, creates, and deploys innovative data-driven solutions for many parts of the enterprise. For more opportunities in data science, please visit our

You will join a team of analytics engineers, to provide clean transformed data for data science solutions. You will build data transformation pipelines which adhere to software and data engineering best-practice standards. You'll be an instrumental member of the Analytics Engineering team, part of the wider MLOps umbrella, led by Boris Simanovich.

Responsibilities:

  1. Partner with data scientists to explore, analyze, and source data from our strategic data sources.
  2. Create data pipelines to provide clean transformed data for data science/analytics use cases.
  3. Follow best practices to coding formats, naming conventions, and version control.
  4. Review code changes and approve pull requests (PRs) in Git
  5. Convert requirements into Jira stories and provide milestones.
  6. Partner with data scientists regarding data quality, availability, value, etc.
  7. Collaborate with data stewards throughout NYL.
  8. Build strong relationships with Technology (IT) to work on tooling, data strategy, integrations, and deployments.
  9. Effectively communicate information and ideas to a diverse group of people
  10. Stay up to date with the latest Analytics Engineering trends/emerging technologies and look for opportunities to improve the stack.

Required qualifications:

  • 3+ years of industry experience in data analytics and/or data engineering
  • Expert in advanced SQL and Python (using dbt or similar tools)
  • Experience with building data models
  • Experience in automating and managing SQL using software engineering best practices.
  • Follow standards and practices for data/analytics engineering (architectural data pipeline patterns)
  • Experience with big data platforms such as Redshift, Snowflake, Hadoop
  • Excellent command of Git
  • Experience with cloud compute environments (AWS, Azure) along with cloud-native tools
  • Experience with Agile/Scrum methodology and best practices
  • Degree in computer science, engineering, or relevant work experience

Preferred:

  • Previous work experience with Data Science/AI teams
  • Exposure to Generative AI and use of unstructured data
  • Insurance industry experience

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