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About This Role
Job Description
-------------------
#### Requisition ID
94549
#### Department
Tech Data AI Ventures
#### Job Function
Tech Data AI Ventures
#### Location
New York,New York,United States
#### Role Location Designation
Hybrid \- 3 days per week
Job Requisition ID: 94549
Location Designation: Hybrid \- 3 days per week
Program Overview:
Within the Tech, Data, AI, Ventures (TDAV) organization, our work is guided by a shared vision: deploying the power of technology, data, AI and ventures to accelerate sustainable competitive advantage for New York Life's businesses. We build solutions that power how we serve policy owners, agents, advisors and employees. Grounded in New York Life’s culture of long\-term commitment, integrity and putting people at the center of what we do, our work reflects a purpose\-driven approach to innovation.
We engineer complex systems that translate into measurable business outcomes. Across technology, data, AI, cyber, product, digital experience, architecture and infrastructure, TDAV combines the scale and investment of an industry leader with the opportunity to work with leading\-edge technologies and help shape how a world\-class financial services company competes in the AI era — all backed by the stability and purpose of a mutual company built to last.
Shape your future with a dynamic internship experience at New York Life. Your internship journey is designed to challenge you through hands\-on work experience that will equip you with valuable skills you can use anywhere. You will build your network through collaboration and connection with talented interns and experienced employees through team\-building activities, a collaborative intern capstone, and fun social events. By the end of your internship, you'll be equipped with new skills and a network that will propel you forward in your career journey.
What You'll Do:
Focus on building scalable data architectures, pipelines, automating data processes, enhancing data quality frameworks, and supporting cloud infrastructure initiatives. Contribute to AWS automation, data warehousing, workflow optimization, and the operationalization of data tools to create efficient systems for processing and transforming structured and unstructured data from multiple sources. Improve data management and governance by leveraging technologies such as advanced analytics, AI, and machine learning to strengthen data curation, enhance data quality, and increase efficiency across the organization's data ecosystem. Support platform integration efforts through developing and maintaining standardized pipelines and frameworks that connect data systems and business applications.
Required Skills:
- Undergraduate or Graduate student pursuing a degree in Computer Science, Management Information Systems, Software Engineering, or a related technical field
- Proficiency in Python, SQL, and understanding of data warehousing principles
- Experience with AWS, dbt, Databricks, Redshift, GCP, Glue, PostgreSQL, and Informatica Data Management Cloud preferred
Eligibility Criteria:
- Currently pursuing a bachelor's or master's degree with an expected graduation date of December 2027 or May 2028
- Available to work full\-time for the entire duration of the 11\-week Summer Internship Program (May 25 \- August 6, 2027\)
- Able to work in a hybrid environment, with three days per week on\-site in New York City
- Passionate about technology, data, AI, and innovation, with a collaborative mindset and a desire to learn and make an impact
*To be eligible for this program, you must be authorized to work in the U.S. We do not offer any type of employment\-based immigration sponsorship for this program. Likewise, this program is not available to those authorized to work under optional practical training (OPT) or curricular practical training (CPT).*
*As part of the Technology, Data \& Analytics Ventures (TDAV) Internship Program, this posting represents one of seven specialized internship opportunities: AI Engineer (MLOps), Software Engineer, Data Engineer, Platform Engineer, Security Engineer, Data Scientist, and Analyst. We encourage candidates to explore all available TDAV internship postings and apply for the role(s) that best align with their skills, interests, and career aspirations.*
Curious what it’s like to intern at NYL? Check out \#NYLEarlyCareers on LinkedIn!
\#AICampus\#LI\-CV1
Pay Transparency
Salary Range: $30\-35/hour \+ $3,000 bonus
Overtime eligible: Exempt
Discretionary bonus eligible: No
Sales bonus eligible: No
Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.
Our Benefits
We provide a full package of benefits for employees – and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work.Click hereto discover more about our comprehensive benefit options or visit our NYL Benefits Site.
Our Commitment to Inclusion
At New York Life, fostering an inclusive workplace is fundamental to who we are and how we serve our communities. We have a longstanding commitment to creating an environment where individuals can contribute their best and succeed together. This foundation is rooted in our core values of humanity and integrity, ensuring that every employee feels valued and supported. By embracing a broad range of perspectives and experiences, we achieve greater success and fulfill our promise of providing financial security and peace of mind to families across all communities. Click here to learn more about New York Life’s leadership in this space.
Recognized as one of *Fortune’s* World’s Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. To learn more about career opportunities at New York Life, please visit the Careers page of www.NewYorkLife.com.
Job Requisition ID: 94549
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Salary Context
This $62K-$72K range is in the lower quartile for Data Engineer roles in our dataset (median: $153K across 35 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 4,317 AI roles we're tracking, Data Engineer positions make up 1% of the market. At New York Life, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills Required
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $185,000 based on 83 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,000. This role's midpoint ($67K) sits 63% below the category median. Disclosed range: $62K to $72K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
New York Life AI Hiring
New York Life has 15 open AI roles right now. They're hiring across AI/ML Engineer, MLOps Engineer, Data Scientist, Data Engineer. Positions span New York, NY, US, White Plains, NY, US. Compensation range: $72K - $230K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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