Location:

CN-Shenzhen-HyQ

Shift:

Standard - 40 Hours (China)

Scheduled Weekly Hours:

40

Worker Type:

Permanent

Job Summary:

Lead the design and delivery of LME market data platforms that consolidate multiple real-time and historical market data sources into scalable enterprise data assets for external and internal consumption. This role focuses on enterprise data management and big data engineering—building robust data lake/warehouse foundations, orchestrated ETL/ELT pipelines, and performant analytics access to support market data commercialisation and business intelligence.

Job Duties:

Key Responsibilities

Market Data & Data Product Enablement

• Partner with product/business stakeholders to define market data product objectives and translate them into data platform deliverables.
• Consolidate, normalise, and curate market data sets (including derivatives and order book datasets) as governed, reusable data assets.
• Define data contracts, metadata, lineage, and quality rules so downstream users can reliably consume market data products.

Enterprise Data Management & Architecture

• Define and evolve enterprise data management architecture across data lake and data warehouse solutions (on-prem and/or cloud).
• Design and operate data lake/warehouse layers using technologies such as ADLS, Amazon S3, Google Cloud Storage, Azure Synapse SQL, Snowflake, Amazon Redshift, or Google BigQuery.
• Set standards for data modelling, governance, security controls, retention, and lifecycle management aligned with organisational policies.

Big Data Engineering & Pipeline Delivery

• Design, build, and maintain scalable ETL/ELT pipelines for analytics and reporting using code-driven patterns and distributed compute engines.
• Implement and operate workflow orchestration frameworks such as Apache Airflow, Prefect ("Perfect"), or Dagster, including scheduling, dependency management, and observability.
• Engineer processing solutions using big data stacks such as Hadoop, Spark, Kafka, and Flink ("Flint"), ensuring throughput, reliability, and cost efficiency.
• Leverage Spark and/or Databricks (built on Spark) to deliver large-scale transformations and performance-tuned workloads.

Data Stores, Query Performance & Reliability

• Design data storage and access patterns across data warehouses and databases, including NoSQL stores (e.g., HBase) and analytical engines (e.g., ClickHouse, Snowflake).
• Drive query and pipeline performance tuning (partitioning, caching, file formats, indexing/cluster keys) and improve SLAs/SLOs for critical datasets.
• Lead incident analysis and root-cause investigations for >

  Company Introduction:

  ITD SZ

  港交所科技（深圳）有限公司，是2016年12月28日于深圳市前海自贸区成立的外商独资企业。

  作为港交所的技术子公司，港交所科技（深圳）有限公司主要是为集团及其附属公司提供计算机软件、计算机硬件、信息系统、云存储、云计算、物联网和计算机网络的开发、技术服务、技术咨询、技术转让；经济信息咨询、企业管理咨询、商务信息咨询、商业信息咨询、信息系统设计、集成、运行维护；数据库管理、大数据分析；以承接服务外包方式提供系统应用管理和维护、信息技术支持管理、数据处理等信息技术和业务流程外包服务。