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 firms 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
Bachelors or Masters 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.
Base Pay and Compensation
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.