Senior Associate - Enterprise Intelligence Analytics Engineer

New York Life Insurance Co•New York, NY

1d•$90,000 - $128,500•Hybrid

About The Position

The Analytics Engineer is a key contributor within the Enterprise Intelligence Data Services team, responsible for developing and maintaining the analytics foundations that power enterprise intelligence, reporting, and AI-driven decision-making. Working closely with senior analytics engineers, data engineers, and business stakeholders, this role helps transform enterprise data into trusted, accessible, and actionable information products. This position combines technical expertise in data transformation and modeling with a strong focus on data quality, business understanding, and collaboration. The successful candidate will contribute to scalable analytics solutions, support reporting and intelligence initiatives, and continue building expertise in modern analytics engineering practices, cloud data platforms, and AI-enabled data ecosystems.

Requirements

Bachelor's degree and 1–3 years of experience in analytics engineering, data engineering, business intelligence, or a related technical field.
Proficiency in SQL with the ability to write, troubleshoot, and optimize queries for data transformation, reporting, and analysis.
Experience with dbt or similar data transformation tools and a foundational understanding of analytics engineering concepts and best practices.
Knowledge of data warehousing principles, dimensional modeling concepts, and data quality management practices.
Strong analytical, problem-solving, and organizational skills with attention to detail and a commitment to delivering accurate, reliable data solutions.
Effective communication and collaboration skills, with the ability to work successfully across technical and business teams in a fast-paced environment.

Nice To Haves

Exposure to cloud data platforms such as Google Cloud Platform (GCP), AWS, Databricks, BigQuery, or similar modern data ecosystems.
Experience developing reports, dashboards, or data visualizations using tools such as Looker, Tableau, Power BI, or related platforms.
Familiarity with Git, version control practices, Agile delivery methodologies, and collaborative software development workflows.
Interest in artificial intelligence, machine learning, enterprise intelligence platforms, and the role of data in enabling advanced analytics and decision-making.

Responsibilities

Develop and maintain data transformation logic, data models, and analytics datasets using SQL, dbt, and modern analytics engineering practices to support enterprise reporting, analytics, and intelligence initiatives.
Contribute to the implementation of data quality controls, testing frameworks, and documentation standards that improve the reliability, consistency, and usability of enterprise data assets.
Support the development and maintenance of dashboards, reports, and business metrics by partnering with analytics teams and stakeholders to deliver actionable insights and trusted information products.
Collaborate with engineering, analytics, and business teams to understand requirements, translate business needs into data solutions, and support the delivery of high-quality data products.
Participate in Agile delivery activities, continuous learning opportunities, and cross-functional initiatives that enhance analytics engineering capabilities, data governance practices, and platform maturity.