Associate - Technology Data Analyst

New York Life • New York, NY

3d • $81,000 - $115,500 • Hybrid

About The Position

As a Technology Data Analyst within New York Life’s AI & Data organization, you will connect business needs, data, and technology. You will analyze complex data requirements, design data solutions, and support reliable, high-quality data pipelines. The role calls for strong analytical skills, an understanding of data architecture, and the ability to translate business questions into actionable data and technical requirements.

You will perform data, business, and technical analysis to design and deliver data solutions aligned with the enterprise AI & Data strategy. The work emphasizes building data products, improving pipelines, ensuring data quality, and enabling analytics and AI use cases. You will collaborate with business, technology, data engineering, analytics, and product teams to deliver scalable solutions that support decision-making, operational efficiency, and client and employee experiences.

The position is hybrid, with three days per week in the workplace. The posted salary range is $81,000–$115,500. The role is exempt and eligible for an annual discretionary bonus; actual base salary depends on factors including experience, skills, qualifications, and job location.

Requirements

• 3–5 years of experience as a Technology Analyst, Data Analyst, or in a similar role supporting enterprise data platforms.
• Strong data analysis and problem-solving skills, including the ability to translate business needs into data-driven solutions.
• Strong SQL experience for data analysis, validation, troubleshooting, and performance optimization.
• Experience with data pipelines, ETL/ELT processes, and data integration workflows.
• Familiarity with Agile/Scrum methodologies and tools such as Jira, Confluence, or DevOps.
• Ability to create clear technical documentation, process maps, and development specifications.
• Excellent communication and collaboration skills to work across teams and organizational levels.
• Strong attention to detail and ability to manage multiple priorities in a fast-paced environment.
• Understanding of end-to-end workflows and integrations, configuration, and connecting processes, platforms, and data to deliver scalable and efficient solutions.
• Critical thinking and ability to communicate complex data concepts clearly.

Nice To Haves

• Understanding of modern data architectures, including data lakes, data warehouses, and cloud-based data platforms.
• Experience supporting analytics, BI, or AI/ML use cases through well-designed data solutions.
• Knowledge of data quality frameworks, data governance, or metadata management practices.
• Exposure to API-based data ingestion, streaming data, or near-real-time data pipelines.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud and their native data services.
• Experience in insurance or financial services and understanding of regulated data environments.

Responsibilities

• Collaborate with business stakeholders, data engineers, and analytics teams to gather and document business, analytical, and data requirements.
• Translate business questions and analytical needs into data specifications, source-to-target mappings, and technical requirements.
• Perform data analysis, profiling, and validation to support data ingestion, transformation, and consumption layers.
• Partner with data engineering teams to design, enhance, and support scalable data pipelines and data products.
• Support the development and maintenance of data models, metric definitions, and semantic layers for reporting and analytics.
• Validate data accuracy, completeness, and timeliness through testing, reconciliation, and monitoring activities.
• Participate in Agile delivery processes, including backlog refinement, sprint planning, and user acceptance testing, with a focus on data readiness.
• Act as a liaison between business users, analytics teams, and data engineers to support shared understanding and successful delivery.
• Identify data gaps, quality issues, and optimization opportunities, and recommend improvements aligned with AI & Data standards.

Benefits

• Full package of employee benefits, including leave programs, adoption assistance, and student loan repayment programs.
• Eligible for an annual discretionary bonus.
• May be eligible to participate in an incentive program.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed