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Lead Architect, Database & Data Automation

Lead Architect, Database & Data Automation

Value Partners LimitedHong Kong
14 天前
职位描述

Job description :

1. Database Architecture Design

  • Lead the design of high-performance, distributed database systems (SQL / NoSQL) optimized for financial data processing, including market feeds, portfolio analytics, middle- / back-office STP and client reporting.
  • Implement Data Quality Monitor, and Unified Reporting Facility.
  • Provide a data portal to allow self service for firms all personnel.
  • Provide data infrastructure to support firm’s AIGC applications.
  • Implement data sharding, replication, and disaster recovery strategies to ensure system reliability in critical trading environments.

2. Data Automation & Pipeline Optimization

  • Develop automated ETL workflows using tools like Apache Airflow or Kafka, integrating with cloud-native services (AWS Glue / Azure Data Factory).
  • Streamline data ingestion from heterogeneous sources (Bloomberg, etnet, Morningstar, custodian / trust, into unified data lakes / warehouses.

    • 3. Cross-functional Collaboration

  • Partner with Investment Management (IM) teams to deploy time-series databases for investment research, quantitative strategy, risk modeling and algorithmic dealings.
  • Collaborate with cybersecurity teams to enforce GDPR / HKMA, and mainland China cross-boarder data privacy standards.

    • 4. Technical Leadership

  • Define dataernance frameworks and metadata management strategies for enterprise-wide consistency.
  • Lead implementing firm-wide data quality monitoring initiatives.
  • Mentor junior engineers on best practices for AI data processing, database tuning, query optimization, and cost-efficient cloud resource allocation.

    • Job Requirement : 1. Education ：

    BS inputer Science, Data Engineering, or related fields.

    2.Experience :

  • 12+ years of dataflow architecture and automation in financial services.
  • Proven expertise in heterogeneous data integration and automation,with scaling petabyte-level financial data systems.

    • 3.Technical Skills :

  • Mastery of PostgreSQL / Oracle, MongoDB / Cassandra, and columnar databases like ClickHouse.
  • Proficiency in Python / Java, Spark / Flink, and infrastructure-as-code tools (Terraform / Ansible).
  • Deep knowledge of cloud-native architectures (AWS RDS / Azure Cosmos DB).
  • Familiarity with MiFID II, SFTR, or other financial data reporting regulations.
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