AI Data Engineer Jobs in New York
AI Data Engineer jobs in New York are among the most active in the country, concentrated in finance, media, healthcare, and enterprise technology, with openings at every level from entry-level associates through principal engineers. New York City dominates hiring volume, with significant demand also coming out of Albany and Buffalo, where state government agencies and regional health systems are building out data infrastructure. Goldman Sachs, JPMorgan Chase, and IBM are among the established New York employers with consistent demand for ai data engineers, particularly in MLOps pipeline development, large language model integration, and real-time data architecture. Find a role that fits below and apply directly.
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About The Role
Schonfeld Strategic Advisors is seeking an experienced AI Data Engineer to join our Data Engineering team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines that power SchonAI, our firm's internal AI platform. You will work at the intersection of data engineering and AI, ensuring that high-quality, timely, and relevant data flows seamlessly to our AI systems to support investment professionals across the firm.
Key Responsibilities
Data Pipeline Development
- Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data to SchonAI using Prefect.
- Develop ETL/ELT processes for diverse data sources including market data, research documents, internal databases, and third-party APIs.
- Implement real-time and batch data processing workflows to meet varying latency requirements.
- Ensure data quality, consistency, and integrity across all pipelines.
AI Data Infrastructure
- Build and maintain data infrastructure optimized for AI/ML workloads, including vector databases and semantic search systems.
- Design data schemas and storage solutions that support efficient retrieval and processing for LLM applications.
- Implement data versioning, lineage tracking, and observability for AI training and inference pipelines.
- Optimize data delivery for low-latency AI interactions and high-throughput batch processing.
Integration & Collaboration
- Partner with AI engineers, software developers, and data scientists to understand data requirements.
- Integrate with existing firm systems including risk platforms, trading systems, portfolio management tools, and research databases.
- Collaborate with infrastructure teams on cloud architecture, security, and compliance requirements.
- Work closely with business stakeholders to prioritize data sources and pipeline enhancements.
Data Governance & Security
- Implement appropriate data access controls, encryption, and compliance measures.
- Ensure adherence to data governance policies and regulatory requirements.
- Monitor and maintain data pipeline performance, reliability, and cost efficiency.
- Document data flows, transformations, and dependencies.
Required Qualifications
Technical Skills
- Programming: Strong proficiency in Python; experience with SQL and at least one other language (e.g. Java, Scala, Go, Rust)
- Data Engineering: 5+ years of experience building production data pipelines using tools like Apache Airflow, Prefect, Dagster, or similar
- Big Data Technologies: Hands-on experience with distributed computing frameworks (Spark, Flink) and modern data platforms
- Cloud Platforms: Proficiency with AWS services (S3, Kubernetes) or equivalent GCP services
- Databases: Experience with both SQL (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB, Elasticsearch)
- AI/ML Data: Understanding of data requirements for ML/AI systems, including experience with vector databases (Pinecone, Weaviate, Qdrant) and embedding pipelines
Preferred Experience
- Experience building data pipelines for LLM applications or RAG (Retrieval Augmented Generation) systems
- Familiarity with financial data sources (market data, fundamental data, alternative data)
- Knowledge of data streaming technologies (Kafka, Kinesis, Pub/Sub)
- Experience of Analytics/Warehouse/OLAP DB (BigQ, SingleStore, RedShift, ClickHouse)
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Understanding of MLOps practices and tools
- Experience with data quality frameworks (Great Expectations, Deequ)
Professional Skills
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related technical field
- Strong problem-solving skills and attention to detail
- Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
- Experience working in fast-paced, collaborative environments
- Self-motivated with ability to manage multiple priorities
Who We Are
Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.
Our Culture
At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.
The base pay for this role is expected to be between $225k and $275k. The expected base pay range is based on information at the time this post was generated. This role may also be eligible for other forms of compensation such as a performance bonus and a competitive benefits package. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications, and experience.
See All 521+ AI Data Engineer Jobs in New York
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Find AI Data Engineer JobsAI Data Engineer Jobs by City in New York
Where New York roles are concentrated, by current openings.
AI Data Engineer Job Market in New York
A snapshot from current New York openings, updated as new roles post.
Who's Hiring
- Amazon40

- Capital One37

- New York Life13

- Bloomberg12

- Spotify11

Top Industries Hiring
- Technology & Software200
- Banking & Financial Services52
- Investment & Asset Management41
- Consulting & Professional Services30
- Fintech20
What New York Employers Look For
The qualifications that appear most often in AI data engineer jobs across New York.
- Bachelor's or master's degree in computer science, data engineering, or a related field
- Proficiency in Python and SQL for building and maintaining data pipelines
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud
- Familiarity with machine learning frameworks including TensorFlow, PyTorch, or Scikit-learn
- Experience designing and deploying ETL workflows and distributed data systems
- Strong understanding of MLOps practices and model deployment in production environments
AI Data Engineer Jobs in New York: Frequently Asked Questions
How do you become a ai data engineer in New York?
Most ai data engineers in New York enter the field with a bachelor's degree in computer science, data science, or a related discipline, though a master's degree is increasingly common for roles at larger financial and technology employers. There is no state-issued license required to work as an ai data engineer in New York. Employers typically look for demonstrated experience with cloud infrastructure, ML pipelines, and data architecture, often validated through project portfolios, certifications from AWS or Google, and internships completed while studying at New York universities.
How much do AI data engineers make in New York?
AI data 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 ai data engineers in New York?
Employers hiring ai data engineers in New York right now include Amazon, Capital One, and New York Life, based on current listings on Migrate Mate as of June 2026. New York's deep concentration of financial institutions, media companies, and large healthcare systems means consistent year-round demand across industries beyond pure technology.
Which New York cities have the most ai data engineer jobs?
New York, New York City, and New York have the most ai data engineer openings in New York. New York City accounts for the largest share by far, driven by its density of financial services firms, advertising technology companies, and enterprise headquarters, while Albany and Buffalo contribute openings tied to state government data initiatives and regional health system expansions.
Are there remote ai data engineer jobs in New York?
Yes, and more than most fields. About 32% of ai data engineer openings tied to New York are remote or hybrid as of June 2026, reflecting how naturally the work lends itself to distributed teams. The most remote-friendly parts of the role tend to be pipeline development, model monitoring, and data architecture design, while roles involving on-premise infrastructure or close collaboration with trading desks are more likely to require in-office presence.
How can I get hired as a ai data engineer in New York with little or no experience?
The most realistic entry path is securing an associate or junior data engineer role at a New York financial services firm or large health system, which often run formal new-graduate programs. JPMorgan Chase and Citigroup run structured technology analyst programs that place candidates into data and AI teams. Building a portfolio of end-to-end pipeline projects on public datasets, earning a cloud certification from AWS or Google, and targeting lateral moves from data analyst or business intelligence roles at New York companies are the clearest ways to get a foothold without prior ai data engineering titles.
Where can I find and apply to ai data engineer jobs in New York?
You can find and apply to ai data engineer jobs in New York on Migrate Mate, which lists current New York openings from employers actively hiring in the state. Find roles that fit your experience and apply directly to each one.
See All 521+ AI Data Engineer Jobs in New York
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