About Millennium
Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.
Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.
Our Israel office is located in the Bursa area of Ramat Gan.
This role is on-site.
As a global firm, proficiency in English is required.
Meet the Team
Core to the health and growth of our business, Millennium’s Information Technology organization develops the flexible, scalable technology and advanced proprietary systems that support the firm’s multi-manager platform. The Core AI Development Team focuses on the engineering environment, data pipelines, and AI systems that help the firm apply Large Language Models in daily workflows, including enterprise retrieval and document intelligence capabilities.
What You'll Do
- Design, build, and maintain scalable ETL and data ingestion pipelines that move documents from diverse source systems, including file shares, object stores, APIs, and databases, into the firm’s AI platform.
- Develop robust document understanding workflows, including parsing, layout analysis, OCR, text extraction, metadata extraction, and normalization across heterogeneous formats such as PDF, Office documents, HTML, and images.
- Implement chunking, cleaning, and enrichment strategies that improve retrieval quality and support downstream RAG systems.
- Build change-detection, deduplication, and incremental update mechanisms to keep large document corpora synchronized efficiently and reliably.
- Engineer pipelines for correctness, throughput, and resilience, with strong handling for malformed inputs, large files, and high-volume processing.
- Establish data quality checks, observability, and metrics so ingestion issues are identified early and resolved quickly.
- Partner with stakeholders to understand source systems and content requirements and translate them into reliable, production-ready ingestion solutions.
- Stay current with advances in AI, LLMs, document AI, and retrieval techniques, and apply relevant improvements to the team’s solutions.
What You Bring
- 4+ years of experience and strong proficiency in Python, including building data pipelines, services, and APIs.
- Hands-on experience designing and developing ETL and data pipeline solutions, including processing large data volumes.
- Experience with document processing and text extraction, including PDF and Office document parsing, OCR, and unstructured content handling.
- Solid understanding of data modeling, transformation, and data quality best practices.
- Experience designing, building, testing, and debugging high-performance, reliable systems.
- Clear communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
- Familiarity with RAG systems and the impact of ingestion on retrieval quality, including chunking strategies, embeddings, and vector stores, is a plus.
About the RoleDataHub Analytics is looking for an experienced Senior Data Engineer to join our growing team. The ideal candidate will have strong expertise in designing, developing, and optimizing scalable data pipelines and data integration solutions, with hands-on experience in Python, Apache Spark, Apache Kafka, and SQL.
- In this role, you will contribute to building reliable, high-performance data solutions that support our regional expansion and AI-driven growth initiatives.Key ResponsibilitiesDesign, develop, and maintain scalable ETL/ELT data pipelines.
- Build and optimize data processing solutions using Python and Apache Spark.
- Develop and maintain real-time and near-real-time data pipelines using Apache Kafka.
- Write and optimize complex SQL queries and data transformation logic.
- Integrate data from multiple structured and unstructured sources.
- Ensure data quality, reliability, and performance across large-scale data environments.
- Troubleshoot pipeline failures, performance bottlenecks, and data inconsistencies.
- Implement monitoring, logging, error handling, and recovery mechanisms.
- Collaborate with data architects, analysts, developers, and business stakeholders to translate requirements into technical solutions.
- Participate in data modeling, solution design, code reviews, and technical discussions.
- Required Qualifications4+ years of professional experience in Data Engineering, ETL, or Data Integration.
- Strong hands-on experience developing ETL/ELT pipelines.
- Proficiency in Python and SQL.
- Hands-on experience with Apache Spark and distributed data processing.
- Experience with Apache Kafka or similar event-streaming technologies.
- Strong understanding of relational databases, data warehouses, and data modeling concepts.
- Experience troubleshooting and optimizing production data pipelines.
- Strong analytical, problem-solving, and communication skills.
- Nice to HaveExperience with Java.
- Experience with Apache NiFi and data flow management.
- Familiarity with cloud platforms such as AWS, Azure, or GCP.
- Experience with Apache Airflow or similar orchestration tools.
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