STEM OPT Analytics Engineer Jobs
Analytics Engineer roles sit squarely within STEM OPT eligibility, letting you extend your F-1 work authorization by 24 months beyond your initial OPT period. Your employer must be enrolled in E-Verify, and your degree in computer science, statistics, mathematics, or a related STEM field must align with the role's CIP code.
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Requisition ID
94236
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
Location Designation: Hybrid - 3 days per week
Role Overview
The Senior Associate, Analytics Engineer is responsible for designing, building, and maintaining scalable analytics engineering solutions that transform enterprise data into trusted, consumable data products that support business intelligence, advanced analytics, and AI-driven decision making. Embedded within the Enterprise Intelligence Platform team, this role partners with business stakeholders, data engineers, data scientists, and machine learning engineers to deliver high-quality analytical datasets and transformation pipelines across modern cloud platforms.
Working with a high degree of independence, this individual leads the delivery of analytics engineering workstreams from source alignment and data modeling through deployment, testing, and operational monitoring. The role combines strong technical expertise in dbt, SQL, Python, and cloud data platforms with a commitment to data quality, governance, and engineering excellence. The successful candidate will contribute to platform standards, mentor peers, and help advance modern analytics engineering practices that enable enterprise-scale AI and intelligence products.
What You'll Do:
- Design, build, and optimize scalable dbt transformation pipelines and analytical data products across cloud data 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.
What You'll Bring:
Required Skills
- 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 large-scale data transformation patterns, along with 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 working 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.
Preferred Skills
- Experience with semantic layer technologies such as dbt Semantic Layer, MetricFlow, Looker LookML, or comparable platforms used to standardize and govern business metrics.
- Familiarity with AI-enabled analytics engineering practices, including LLM-assisted development, agentic workflows, automated anomaly detection, and intelligent data quality remediation.
- Experience with data observability, lineage, and governance platforms such as Monte Carlo, Dataplex, DataHub, Alation, or similar technologies.
- Exposure to graph-based data models, knowledge graphs, context graph architectures, or AI-enabled data platforms supporting advanced analytics and machine learning use cases.
- Insurance, financial services, or highly regulated industry experience with knowledge of data privacy, governance, and enterprise compliance requirements.
Pay Transparency
Salary Range: $124,000-$177,000
Overtime eligible: Exempt
Discretionary bonus eligible: Yes
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.
Company Overview
At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact.
Our diverse business portfolio creates opportunities to make a difference across industries and communities—inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you’ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress.
As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what’s next, and your growth powers it.
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 here to 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.
Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities.
Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients' and employees’ needs.
Job Requisition ID: 94236
Job Description
Requisition ID
94236
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
Location Designation: Hybrid - 3 days per week
Role Overview
The Senior Associate, Analytics Engineer is responsible for designing, building, and maintaining scalable analytics engineering solutions that transform enterprise data into trusted, consumable data products that support business intelligence, advanced analytics, and AI-driven decision making. Embedded within the Enterprise Intelligence Platform team, this role partners with business stakeholders, data engineers, data scientists, and machine learning engineers to deliver high-quality analytical datasets and transformation pipelines across modern cloud platforms.
Working with a high degree of independence, this individual leads the delivery of analytics engineering workstreams from source alignment and data modeling through deployment, testing, and operational monitoring. The role combines strong technical expertise in dbt, SQL, Python, and cloud data platforms with a commitment to data quality, governance, and engineering excellence. The successful candidate will contribute to platform standards, mentor peers, and help advance modern analytics engineering practices that enable enterprise-scale AI and intelligence products.
What You'll Do:
- Design, build, and optimize scalable dbt transformation pipelines and analytical data products across cloud data 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.
What You'll Bring:
Required Skills
- 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 large-scale data transformation patterns, along with 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 working 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.
Preferred Skills
- Experience with semantic layer technologies such as dbt Semantic Layer, MetricFlow, Looker LookML, or comparable platforms used to standardize and govern business metrics.
- Familiarity with AI-enabled analytics engineering practices, including LLM-assisted development, agentic workflows, automated anomaly detection, and intelligent data quality remediation.
- Experience with data observability, lineage, and governance platforms such as Monte Carlo, Dataplex, DataHub, Alation, or similar technologies.
- Exposure to graph-based data models, knowledge graphs, context graph architectures, or AI-enabled data platforms supporting advanced analytics and machine learning use cases.
- Insurance, financial services, or highly regulated industry experience with knowledge of data privacy, governance, and enterprise compliance requirements.
Pay Transparency
Salary Range: $124,000-$177,000
Overtime eligible: Exempt
Discretionary bonus eligible: Yes
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.
Company Overview
At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact.
Our diverse business portfolio creates opportunities to make a difference across industries and communities—inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you’ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress.
As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what’s next, and your growth powers it.
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 here to 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.
Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities.
Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients' and employees’ needs.
Job Requisition ID: 94236
See all 2,907+ STEM OPT Analytics Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Analytics Engineer Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as an Analytics Engineer
Verify your CIP code before applying
Pull your degree's Classification of Instructional Programs code from your transcript or DSO and cross-reference it against STEM-designated program lists. Analytics Engineer roles typically align with CIP codes in computer science, mathematics, or information science fields.
Filter job listings by E-Verify status
Before submitting any application, confirm the employer is enrolled in E-Verify through the official E-Verify employer search. Employers who haven't enrolled can't legally employ you on a STEM OPT extension, no matter how willing they are to hire.
Frame your data stack in the resume
Analytics Engineer roles are highly technical. Listing specific tools like dbt, Airflow, or Snowflake signals that you can contribute without a long ramp-up, which directly addresses employer hesitation around the I-983 training plan timeline.
Use Migrate Mate to target employers with STEM OPT history
Search Analytics Engineer openings on Migrate Mate, which surfaces employers with verified STEM OPT and E-Verify enrollment history. That narrows your list to companies that have already cleared the compliance requirements you need.
Submit your I-983 training plan before your OPT end date
Your DSO must receive a complete I-983 outlining your Analytics Engineer responsibilities, learning objectives, and supervision structure. USCIS requires this before your 24-month STEM extension can be authorized, so don't wait until after the offer is signed.
Check whether cap-gap coverage applies if H-1B is filed
If your employer files an H-1B visa petition before your OPT expires, cap-gap rules may automatically extend your work authorization through September 30. Confirm the exact dates with your DSO and track your receipt notice from USCIS closely.
Frequently Asked Questions
Does an Analytics Engineer role qualify for the STEM OPT extension?
Yes, if your degree is in a STEM-designated field such as computer science, statistics, mathematics, or information systems, and the Analytics Engineer role requires that technical background. Your DSO will verify the CIP code match. The role must also involve applying that STEM knowledge directly, not just adjacent business functions. O*NET classifies Analytics Engineer work under data and computer science occupations, which consistently align with STEM OPT eligibility.
What does the employer need to do to hire me on STEM OPT?
The employer must be enrolled in E-Verify before your STEM OPT extension begins. They also need to sign your I-983 training plan, which outlines your role, the skills you'll develop, your compensation, and how your supervisor will oversee your work. USCIS requires that the training plan reflect a genuine mentorship or development structure tied to your STEM degree, not just a standard employment description.
How do I find Analytics Engineer employers enrolled in E-Verify?
You can search the E-Verify employer database directly to confirm enrollment before applying. Migrate Mate also filters Analytics Engineer listings by employers with verified E-Verify enrollment and STEM OPT hiring history, which cuts down the research time significantly. Targeting companies with that track record reduces the risk of an offer falling through because of compliance gaps discovered after the process has already started.
What goes into the I-983 training plan for an Analytics Engineer?
The I-983 must describe your specific Analytics Engineer responsibilities, the STEM skills you'll build during the extension period, your salary and hours, your supervisor's qualifications, and how the employer will evaluate your progress. USCIS expects the plan to demonstrate a direct connection between the work and your STEM degree field. Vague job descriptions that could apply to any data role are a common reason DSOs request revisions before signing.
Can I stay and work if my H-1B petition is filed before my STEM OPT expires?
Yes. If your employer files a timely and properly selected H-1B petition before your STEM OPT authorization ends, cap-gap provisions under USCIS rules extend your work authorization automatically through September 30 of that fiscal year. Your EAD may show an earlier expiration date, but the cap-gap extension is what legally covers you. Carry your H-1B receipt notice and your expired EAD together as documentation during that period.