Senior Associate, Analytics Engineer
Senior
Analytics
Big Data
Business Intelligence
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Governance
Data Integration
Data Management
Data Modeling
Data Observability
Data Pipeline
Data Pipelines
Data Platform
Data Visualization
Data Warehouse
Database
Databases
Databricks
ETL
Integration
Reporting and Analytics
Semantic Layer
SQL
Job Description
Senior Associate, Analytics Engineer at New York Life, hybrid in New York, NY, embedded in the Enterprise Intelligence Platform team to design, build, and maintain scalable analytics engineering solutions and data products for business intelligence, analytics, and AI driven decision making.
Responsibilities
- Design, build, and optimize scalable dbt transformation pipelines and analytical data products across cloud platforms, delivering trusted datasets, dimensional models, feature tables, and business ready data assets that support reporting, analytics, and AI use cases.
- Own data products throughout their lifecycle, including source alignment, modeling, testing, documentation, deployment, monitoring, and continuous improvement, ensuring performance, reliability, governance, and downstream usability.
- Implement and enhance data quality, observability, and governance practices through automated testing, source freshness validation, lineage documentation, metadata management, and compliance with enterprise data standards.
- Contribute to analytics engineering platform capabilities by developing reusable dbt macros, modeling patterns, semantic layer definitions, and automation accelerators that improve consistency, scalability, and delivery efficiency across teams.
- Collaborate with business stakeholders, data stewards, engineers, and data scientists to translate requirements into well-defined solutions, resolve data challenges, support Agile delivery processes, and promote analytics engineering best practices through mentorship and code reviews.
Requirements
- Bachelor's degree and 4+ years of progressive experience in data engineering, analytics engineering, or a related discipline, with a strong focus on production-scale data transformation and analytics platforms.
- Deep expertise in SQL, including complex joins, window functions, common table expressions, query optimization, and proficiency in Python for data engineering tasks.
- Hands-on experience with dbt, including layered modeling, incremental processing, source definitions, testing frameworks, reusable macros, documentation, and multi-environment deployment strategies.
- Experience with modern cloud data platforms such as Databricks and/or BigQuery, with a strong understanding of ELT architectures, dimensional modeling, and analytical data product design.
- Knowledge of software engineering best practices, including Git-based development workflows, code reviews, CI/CD integration, automated testing, and Agile delivery methodologies.
- Strong communication, problem-solving, and stakeholder management skills, with the ability to translate business requirements into scalable technical solutions and effectively collaborate across technical and non-technical teams.
Technologies
- dbt
- SQL
- Python
- Databricks
- BigQuery
- Git
- CI/CD
- Looker LookML
- dbt Semantic Layer
- MetricFlow
- Monte Carlo
- Dataplex
- DataHub
- Alation
Benefits
- Leave programs
- Adoption assistance
- Student loan repayment programs
Pay Transparency
- Salary Range: $124,000-$177,000 per year
- Overtime eligible: Exempt
- Discretionary bonus eligible: Yes
- Sales bonus eligible: No
- Base salary is determined by factors including experience, skills, qualifications, and location; employees may be eligible for an annual discretionary bonus and may participate in incentive programs.
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