Data Analytics Engineer Jobs in New York
Data Analytics Engineer jobs in New York are in high demand, with openings concentrated in financial services, media and advertising, healthcare systems, and large-scale e-commerce, at every level from entry-level analyst through senior engineer. The heaviest hiring runs through New York City, with additional activity in Albany and Buffalo as state agencies and regional tech employers grow their data teams. Well-established employers with lasting New York footprints include JPMorgan Chase, IBM, and NBCUniversal, and the most sought-after specialties are data pipeline architecture, cloud-based ETL development, and analytics platform engineering. Find a role that fits below and apply directly.
Find Data Analytics Engineer JobsOverview
Showing 5 of 117+ Data Analytics Engineer jobs
- Advises the Product Solutions teams on solutioning and adopting new and existing client-facing products and capabilities while crafting complex solutions and assessing risk to enhance the customer experience
- Leverages extensive knowledge of a cluster of products and capabilities to manage the strategic development of end-to-end product solution strategies and processes
- Partners with Sales to advise on strategic pricing for deals, contributes to the development of sales training and collateral, and oversees Request for Proposal (RFP) responses
- Manages the collection of client feedback and oversees the delivery of feedback to Product teams
- Drives the development of strategy and roadmaps for data governance initiatives, including next-generation data governance tooling and AI-for-data capabilities
- Collaborates with stakeholders, subject matter experts, and engineers to understand use cases, requirements, and dependencies, critically assessing proposed solutions.
- Communicates complex ideas effectively to collaborators and senior leaders using precise terminology and relatable examples
- Balances timeliness with quality under tight deadlines, managing multiple priorities and cross-functional partnerships.
- Ensures end-to-end relevance to stakeholder needs, from gathering business requirements and working with technology teams to achieve successful delivery
- Defines and refines customer-centric solution approaches that connect data governance capabilities to measurable business outcomes.
- Partners with business, technology, and control stakeholders to deploy solutions into production effectively and responsibly
- 8+ years of experience or equivalent expertise leading and developing solutions across multiple teams and a cluster of products
- Extensive experience facilitating sales cycle activities and developing and optimizing strategies and processes
- Demonstrable experience structuring and handling complex solutions for business problems to meet clients' needs
- Understanding and hands-on experience building agentic AI systems within regulated or compliance-driven environments
- 8+ years of experience developing enterprise-wide data, data governance, or AI strategy for large, complex organizations.
- 8+ years of experience either as a product manager, product designer, engineer, data analyst, data scientist, or user researcher
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Curious, hardworking, and detail-oriented, and motivated by complex analytical problems.
- Ability to collaborate effectively with stakeholders, subject matter experts, and engineers to translate needs into clear requirements
- Ability to balance quality and speed under tight deadlines while managing multiple priorities and partnerships.
- Ability to drive end-to-end delivery—from business requirements through implementation—ensuring outcomes meet stakeholder needs
- Direct experience with MCP (Model Context Protocol) designing tool schemas, building MCP servers, managing tool surface exposure, or integrating MCP into an agent platform
- Experience in regulated industries (financial services, healthcare, or government) with practical exposure to model risk management, audit trails, and compliance-driven engineering constraints.
- Familiarity with agent security concerns: prompt injection, tool misuse, over-privileged tool access, and blast radius containment strategies
- Experience building evaluation frameworks for LLM-based systems, including production-grade evaluation pipelines with structured outputs and regression tracking.
- Exposure to cloud-native AI infrastructure (managed model endpoints, model gateways, token/cost observability, and multi-tenant serving considerations)
- Experience contributing to developer-facing SDK or platform tooling (designing APIs, writing effective documentation, iterating based on adoption signals).
- Familiarity with responsible AI practices as they apply to agents, including human oversight requirements, escalation paths, intervention hooks, and auditability standards
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
- Advises the Product Solutions teams on solutioning and adopting new and existing client-facing products and capabilities while crafting complex solutions and assessing risk to enhance the customer experience
- Leverages extensive knowledge of a cluster of products and capabilities to manage the strategic development of end-to-end product solution strategies and processes
- Partners with Sales to advise on strategic pricing for deals, contributes to the development of sales training and collateral, and oversees Request for Proposal (RFP) responses
- Manages the collection of client feedback and oversees the delivery of feedback to Product teams
- Drives the development of strategy and roadmaps for data governance initiatives, including next-generation data governance tooling and AI-for-data capabilities
- Collaborates with stakeholders, subject matter experts, and engineers to understand use cases, requirements, and dependencies, critically assessing proposed solutions.
- Communicates complex ideas effectively to collaborators and senior leaders using precise terminology and relatable examples
- Balances timeliness with quality under tight deadlines, managing multiple priorities and cross-functional partnerships.
- Ensures end-to-end relevance to stakeholder needs, from gathering business requirements and working with technology teams to achieve successful delivery
- Defines and refines customer-centric solution approaches that connect data governance capabilities to measurable business outcomes.
- Partners with business, technology, and control stakeholders to deploy solutions into production effectively and responsibly
- 8+ years of experience or equivalent expertise leading and developing solutions across multiple teams and a cluster of products
- Extensive experience facilitating sales cycle activities and developing and optimizing strategies and processes
- Demonstrable experience structuring and handling complex solutions for business problems to meet clients' needs
- Understanding and hands-on experience building agentic AI systems within regulated or compliance-driven environments
- 8+ years of experience developing enterprise-wide data, data governance, or AI strategy for large, complex organizations.
- 8+ years of experience either as a product manager, product designer, engineer, data analyst, data scientist, or user researcher
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Curious, hardworking, and detail-oriented, and motivated by complex analytical problems.
- Ability to collaborate effectively with stakeholders, subject matter experts, and engineers to translate needs into clear requirements
- Ability to balance quality and speed under tight deadlines while managing multiple priorities and partnerships.
- Ability to drive end-to-end delivery—from business requirements through implementation—ensuring outcomes meet stakeholder needs
- Direct experience with MCP (Model Context Protocol) designing tool schemas, building MCP servers, managing tool surface exposure, or integrating MCP into an agent platform
- Experience in regulated industries (financial services, healthcare, or government) with practical exposure to model risk management, audit trails, and compliance-driven engineering constraints.
- Familiarity with agent security concerns: prompt injection, tool misuse, over-privileged tool access, and blast radius containment strategies
- Experience building evaluation frameworks for LLM-based systems, including production-grade evaluation pipelines with structured outputs and regression tracking.
- Exposure to cloud-native AI infrastructure (managed model endpoints, model gateways, token/cost observability, and multi-tenant serving considerations)
- Experience contributing to developer-facing SDK or platform tooling (designing APIs, writing effective documentation, iterating based on adoption signals).
- Familiarity with responsible AI practices as they apply to agents, including human oversight requirements, escalation paths, intervention hooks, and auditability standards
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
See All 117+ Data Analytics Engineer Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
Find Data Analytics Engineer JobsData Analytics Engineer Jobs by City in New York
Where New York roles are concentrated, by current openings.
Data Analytics Engineer Job Market in New York
A snapshot from current New York openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Insurance
- Education
- Science & Research
- Sports & Recreation
What New York Employers Look For
The qualifications that appear most often in data analytics engineer jobs across New York.
- Bachelor's degree in computer science, data engineering, statistics, or a closely related field
- Proficiency in SQL and at least one scripting language such as Python or Scala
- Hands-on experience building and maintaining ETL or ELT data pipelines at scale
- Familiarity with cloud data platforms such as Snowflake, BigQuery, or AWS Redshift
- Experience with workflow orchestration tools such as Apache Airflow or dbt
- Strong understanding of data modeling, schema design, and data warehouse best practices
Data Analytics Engineer Jobs in New York: Frequently Asked Questions
How do you become a data analytics engineer in New York?
Data analytics engineer roles in New York require no state-issued license or registration, so the path runs through education and demonstrated technical skill. Most New York employers expect a bachelor's degree in computer science, data science, or a related field, though strong portfolio projects and cloud certifications from providers such as AWS, Google Cloud, or Snowflake carry real weight. New York's dense tech and finance sectors mean candidates who show experience with high-volume data systems move to the front of hiring queues quickly.
How much do data analytics engineers make in New York?
Data analytics engineers in New York earn a median of about $130,460 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $73,330 for the lowest 10% to over $214,080 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data analytics engineers in New York?
Employers hiring data analytics engineers in New York right now include JPMorganChase, American Express, and Capital One, based on current listings on Migrate Mate as of September 2026. New York's concentration of financial institutions, media companies, and large healthcare networks means demand comes from a particularly wide range of industries compared to most U.S. markets.
Which New York cities have the most data analytics engineer jobs?
New York, Albany, and Syracuse account for the most data analytics engineer openings in New York. New York City dominates because of its dense concentration of financial services firms, advertising technology companies, and major healthcare systems, while Albany draws openings from state government agencies and insurers, and Buffalo has seen growth from regional banks and expanding university-affiliated research operations.
Are there remote data analytics engineer jobs in New York?
Yes, and more than most fields. About 85% of data analytics engineer openings tied to New York are remote or hybrid as of September 2026, reflecting how well-suited the core work is to distributed environments. The parts of the role most commonly offered remotely are pipeline development, data modeling, and analytics platform maintenance, while positions that require close collaboration with on-site data infrastructure or trading systems tend to stay in-office.
How can I get hired as a data analytics engineer in New York with little or no experience?
The most realistic entry path is a junior or associate data engineer role, often reached by lateral moves from business analyst, data analyst, or SQL-heavy reporting positions that New York's financial and media employers hire in volume. Large New York institutions such as JPMorgan Chase and Pfizer run structured new-graduate rotational programs in data and technology that place candidates without direct pipeline experience. Building a public portfolio on GitHub demonstrating ETL work and earning a cloud-platform certification strengthens applications significantly for candidates still building their professional history.
Where can I find and apply to data analytics engineer jobs in New York?
You can find and apply to data analytics engineer jobs in New York on Migrate Mate, which lists current New York openings updated in real time. Search the listings, find roles that match your experience and location, and apply directly to the ones that fit.
See All 117+ Data Analytics Engineer Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
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