Vice President - LME Data Platform
Hong Kong Exchanges and Clearing Limited4 months ago
Shenzhen, ChinaStaff+
Responsibilities
- Partner with product and business stakeholders to define market data product objectives and platform deliverables.
- Consolidate, normalize, curate, and govern real-time and historical market data, including derivatives and order book datasets.
- Define data contracts, metadata, lineage, quality rules, governance, security controls, retention, and lifecycle standards.
- Design and operate enterprise data lake and data warehouse architectures across on-premises and cloud environments.
- Build and maintain scalable ETL/ELT pipelines using distributed compute engines and workflow orchestration frameworks.
- Engineer large-scale processing solutions using Hadoop, Spark, Kafka, Flink, and Databricks.
- Design data storage and access patterns across warehouses, databases, NoSQL stores, and analytical engines.
- Tune query and pipeline performance through partitioning, caching, file formats, indexing, and cluster keys.
- Lead incident analysis and root-cause investigations and implement reliability improvements for critical datasets.
- Provide hands-on technical leadership, coaching, engineering standards, documentation, monitoring, automated testing, and delivery coordination with global engineering and infrastructure teams.
Requirements
- Degree in Computer Science, IT, Data Engineering, or a related discipline, or equivalent practical experience.
- Typically 12+ years of experience delivering enterprise data management and big data platforms.
- Proven experience leading delivery, making architecture decisions, and managing stakeholders across cross-functional teams.
- Experience designing and operating data lakes and warehouses using technologies such as ADLS, Amazon S3, Google Cloud Storage, Azure Synapse SQL, Snowflake, Amazon Redshift, or Google BigQuery.
- Experience with Hadoop, Spark, Kafka, Flink, Airflow, Prefect, Dagster, and/or Databricks.
- Experience with NoSQL databases, HBase, ClickHouse, Snowflake, SQL, and performance tuning.
- Proficiency in at least one data engineering programming language such as Python, Scala, or Java; Java experience is beneficial but not mandatory.
- Strong analytical, problem-solving, communication, prioritization, stakeholder management, accountability, and proactive delivery skills.
- Experience in financial services, exchanges, or regulated environments is advantageous.
Tech Stack
Amazon RedshiftApache AirflowApache FlinkApache HadoopApache HBaseApache KafkaApache SparkClickHouseDatabricksGoogle BigQueryGoogle CloudJavaPythonScalaSnowflakeSQL
Categories
Data Engineering