Description :
Key Responsibilities :
- Architect and maintain structured databases for tick-level and MFT data.
- Develop efficient ingestion & ETL pipelines using Python / C++, handling large volumes in near-real time.
- Write optimised SQL queries and manage schemas for time-series and reference data.
- Implement automated data validation, reconciliation, and version control.
- Work with quants to expose clean datasets for research and live trading systems.
- Ensure data integrity across time zones, instruments, and asset classes.
- Manage historical data archives and set up policies for retention, compression, and retrieval.
- Collaborate with the execution team to align live feeds with stored data.
Requirements :
Skills & Qualifications :
Strong command over Python (pandas, multiprocessing, asyncio) and SQL (Postgres / MySQL).Working knowledge of C++ for performance-critical modules or parsers.Comfort with Linux environments, shell scripting, and version control (Git).Experience handling large-scale time-series data.Understanding of data normalization, schema design, and storage optimization.Ability to work independently, manage priorities, and deliver with accountability.Exposure to financial or tick-data pipelines, FIX / FAST feeds, or exchange APIs.Familiarity with Redis, Kafka.Prior experience in an HFT, quant, or data-heavy product firm(ref : hirist.tech)