Senior Associate - Analytics Engineer

New York Life•New York, NY

2d•$100,000 - $143,000•Hybrid

About The Position

Join NYL Enterprise Intelligence as an Analytics Engineer on the Data Services team. This is a foundational role within one of the most innovative, founder-mode organizations inside New York Life — a team on a mission to transform 178 years of proprietary data into bleeding-edge AI intelligence, embedded at the point of every decision. You will work at the intersection of data engineering and business insight, building the analytics foundations that power enterprise-scale intelligence products across every line of business. The Analytics Engineer contributes to the development and maintenance of data transformation logic, data models, and analytics solutions that sit at the heart of NYL’s Enterprise Intelligence platform. Working under the guidance of senior engineers, you will help ensure that data is accurate, accessible, and actionable — enabling the decisioning and AI capabilities that drive measurable business impact across the enterprise.

Requirements

1–3 years of experience in analytics engineering, data engineering, or a related field.
Proficiency in SQL, including writing and optimizing queries for data transformation and analysis.
Familiarity with data warehousing concepts and analytics best practices.
Strong attention to detail and commitment to data quality, accuracy, and reliability.
Ability to work collaboratively in a fast-paced, team-oriented environment, building effective relationships across engineering, analytics, and business teams.

Nice To Haves

Experience with dbt or similar data transformation tools.
Exposure to cloud data platforms such as GCP, AWS, Databricks, or BigQuery.
Experience with BI and visualization tools such as Looker, Tableau, or similar platforms.
Interest in AI, machine learning, and enterprise intelligence applications.

Responsibilities

Contribute to the development of data transformation logic and maintain existing data models using dbt and SQL.
Write and optimize SQL queries for data transformation and analysis to support accurate, accessible, and actionable data.
Assist in implementing and maintaining data quality checks and testing procedures.
Contribute to documentation of data models, transformations, and business logic to support consistency, reliability, and maintainability.
Develop and maintain reports and dashboards using visualization tools to surface actionable insights.
Support the delivery of business and operational metrics in partnership with Analytics and senior team members.
Work jointly with team members and stakeholders to accomplish shared outcomes.
Participate in cross-functional meetings to understand business requirements and translate them into data needs.
Build collaborative relationships across engineering and analytics teams, contributing to shared outcomes and the continued development of enterprise intelligence capabilities.