AI Data Engineer

Reposted One Month Ago
New York, NY, USA
In-Office
225K-275K Annually
Senior level
Consulting • Quantitative Trading
The Role
The AI Data Engineer will design and implement data pipelines, build AI-optimized data infrastructure, ensure data quality, and collaborate with teams to support AI applications.
Summary Generated by Built In

About the Role

Schonfeld Strategic Advisors is seeking an AI Data Engineer to help build the data and analytics foundation powering our growing agentic AI capabilities. This is a hands-on role that sits at the intersection of AI, data engineering, and data science: you will build the pipelines and datasets that feed our internal AI platform, dig into the data itself to analyze it and engineer features, and help shape how it is used for modeling and investment research. We're looking for someone equally comfortable designing robust data solutions and exploring data to uncover insights, and who is passionate about applying these skills to complex data problems alongside our investment teams.

Key Responsibilities

Data Pipeline Development

  • Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data.
  • Implement real-time and batch data processing workflows to meet varying latency requirements.
  • Ensure data quality, consistency, and integrity across all pipelines.

Data Analysis

  • Explore, clean, and analyze new and existing datasets to build a deep understanding of their structure, quality, and potential applications.
  • Engineer features and curate research-ready datasets for training, fine-tuning, and model evaluation.
  • Conduct exploratory analysis to assess data coverage, surface insights, and validate suitability for research and AI use cases.

AI Data Infrastructure

  • Build and maintain data infrastructure 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.
  • Contribute to data versioning, lineage tracking, and observability for AI training and inference pipelines.

Integration & Collaboration

  • Partner with cross-functional teams, including AI engineers, researchers, and business stakeholders, to understand data needs and design solutions.
  • Collaborate with infrastructure teams on cloud architecture, security, and compliance requirements.

Required Qualifications

Technical Skills

  • Programming: Strong proficiency in Python and SQL (experience with an additional language such as Java, Scala, or Go is a plus)
  • Pipeline Development: Building and orchestrating production data pipelines and ETL/ELT workflows (e.g., Apache Airflow, Prefect, Dagster)
  • Data Modeling & Storage: Designing schemas and working with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Elasticsearch)
  • Data Analysis & Modeling: Analyzing data and building models with statistical/ML libraries (e.g., XGBoost, PyTorch, TensorFlow), including feature engineering, training, and evaluation
  • Cloud Platforms: Working with a major cloud provider (AWS, GCP, or Azure) and core storage and compute services
  • AI/ML Data: Preparing and serving data for ML/AI systems, including vector databases (e.g., Pinecone, Weaviate, Qdrant) and embedding pipelines

Preferred Experience

  • Financial domain knowledge — e.g., quantitative research or data science experience at a buy-side or sell-side firm
  • Experience supporting LLM applications or RAG (Retrieval Augmented Generation) systems
  • Familiarity with distributed computing frameworks (Spark, Flink) or large-scale data platforms
  • Familiarity with financial data sources (market data, fundamental data, alternative data)
  • Knowledge of data streaming technologies (Kafka, Kinesis, Pub/Sub)
  • Experience with data quality frameworks (Great Expectations, Deequ)

Professional Skills

  • Bachelor's, Master's, or PhD in Computer Science, Data Science, or a related 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.

#LI-PW1

__PRESENT

Skills Required

  • Strong proficiency in Python
  • 5+ years of experience building production data pipelines
  • Hands-on experience with distributed computing frameworks
  • Proficiency with AWS services or equivalent GCP services
  • Experience with both SQL and NoSQL databases
  • Understanding of data requirements for ML/AI systems
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The Company
HQ: New York, NY
515 Employees
Year Founded: 1988

What We Do

Schonfeld Strategic Advisors is a global multi-manager platform that invests its capital with Internal and Partner portfolio managers, primarily on an exclusive or semi-exclusive basis, across quantitative, fundamental equity and tactical trading strategies. We have created a unique structure to provide global portfolio managers with autonomy, flexibility and support to best enable them to maximize the value of their businesses. Over the last 30+ years, Schonfeld has successfully capitalized on inefficiencies and opportunities within the equity markets. We have developed and invested heavily in proprietary technology, infrastructure and risk analytics. Our portfolio exposure has expanded across the Americas, Europe and Asia as well as multiple asset classes and products. We look for ways to align the interests of investors, investment professionals and the firm, highlighted by the opportunity for investment professionals to co-invest in our funds and their individual strategies.

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