Data Engineer

Role Overview

Build distributed time-series and vector databases, design data pipelines and integrate third-party market & recruitment data via API connections.

Key Responsibilities

• Architect and maintain robust ETL/ELT data pipelines capable of handling terabytes of financial data.
• Deploy and optimize distributed databases, including time-series (TimescaleDB) and vector stores (Milvus, Pinecone).
• Integrate external financial APIs (Bloomberg, Reuters) and internal proprietary systems.
• Ensure data quality, reliability, and low-latency access for research teams.
• Implement data governance, security, and versioning best practices.

Required Qualifications

• 4+ years of experience in data engineering, data architecture, or backend software engineering.
• Proficiency in Python, Java, or Scala.
• Extensive experience with cloud data platforms (AWS/GCP) and distributed streaming (Kafka, Spark, Flink).
• Expertise in SQL and NoSQL database administration and performance tuning.

Preferred Qualifications & Skills

• Experience integrating with vector databases and LLM frameworks (LangChain, LlamaIndex).
• Knowledge of financial market data infrastructure and low-latency systems.