Head of Data - Global Financial Institution - Hong Kong

NLS Executive Search

Hong Kong

On-site

HKD 1,200,000 - 1,800,000

Full time

14 days+
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Job summary

NLS Executive Search, on behalf of a client, seeks a Data Engineering Lead to design, build and operate data platforms supporting trading, risk and analytics. You will lead a small data team, partner with stakeholders across Trading, Quant/Research, Risk and Technology, and drive engineering best practices for scalability and operational excellence.

You will own end-to-end data pipelines, build scalable architectures, and ensure data quality, governance, and production readiness, while

Qualifications

  • 8+ years of data engineering / data platform experience.
  • Proficient in Python and SQL.
  • Proven track record designing and operating production data pipelines.
  • Strong experience with modern data tooling and data governance concepts.
  • Experience in monitoring, reliability, and operational practices for data workloads.
  • Experience in trading environments (market data, risk data).
  • Cloud exposure and infrastructure-as-code knowledge (Terraform).
  • Experience leading teams or mentoring engineers.

Responsibilities

  • Lead end-to-end development of data pipelines (batch/streaming) for market, reference, and trade data.
  • Design scalable data architectures (lakehouse/warehouse) for accessible, governed data.
  • Own data ingestion from internal/external sources and manage end-to-end data flow reliability.
  • Implement data quality checks, reconciliation, and monitoring.
  • Build data products for dashboards, research, reporting, and risk analytics.
  • Ensure production readiness: monitoring, incident response, runbooks, CI/CD.

Skills

Python
SQL
Data pipelines
Data governance
Monitoring/ops
Cloud platforms
Team leadership
Stakeholder collaboration

Tools

Terraform
AWS/Azure/GCP

Job description

Our client, a global trading firm, is actively seeking a Data Engineering Lead to lead the design, build, and operation of data platforms and pipelines that support their trading business. This role focuses on reliable data ingestion, processing, quality, and delivery to analytics and trading/risk use cases. You will lead a small data team and partner with stakeholders across Trading, Quant/Research, Risk, and Technology to drive engineering best practices around scalability, performance, and operational excellence.

The role:
  • Lead the end-to-end development of data pipelines (batch and/or streaming) for market, reference, and trade-related datasets.
  • Design and maintain scalable data architectures (e.g., lakehouse/warehouse patterns), ensuring data is accessible, governed, and performant.
  • Own data ingestion from internal/external sources (APIs, files, message buses, vendor feeds) and manage end-to-end data flow reliability.
  • Implement and oversee data quality checks, reconciliation, and monitoring (e.g., completeness, accuracy, latency, schema validation).
  • Build data products for downstream consumption (dashboards, research environments, reporting, risk analytics), working closely with business users.
  • Ensure production readiness: operational monitoring, incident response, runbooks, SLA/SLO alignment, and robust CI/CD.
  • Lead engineering practices: code reviews, standards, reusable components, documentation, and mentoring.
  • Collaborate with stakeholders to translate business requirements into technical roadmaps and measurable outcomes.
What you offer:
  • 8+ years of experience in data engineering / data platform engineering
  • Strong hands‑on experience in Python and SQL
  • Proven experience designing and operating data pipelines in a production environment
  • Strong experience with modern data tooling
  • Excellent understanding of data modeling and governance concepts
  • Strong experience with monitoring and operational practices for data workloads
  • Experience in trading environments (market data, order/trade lifecycle, P&L/risk data, reference data)
  • Cloud exposure (AWS/Azure/GCP) and infrastructure-as-code (Terraform) knowledge
  • Experience leading teams and/or mentoring engineers
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