Data Engineering Lead, Middle Office Technology (AVP)

该职位来源于猎聘 Job Summary: We are seeking an experienced data engineering leader to drive the development and optimization of middle office technology systems. This role requires deep technical expertise in big data technologies, strong domain knowledge in banking operations, finance accounting, and regulatory compliance, combined with leadership capabilities to guide a high-performing engineering team. You will collaborate closely with operations teams, finance, risk, and compliance to ensure our data platforms are efficient, scalable, and business-aligned. Key Responsibilities:

• Data Architecture Leadership: Lead the design and development of scalable data pipelines, data warehouses, and analytics platforms supporting trading operations, settlements, and accounting functions.
• Performance & Optimization: Drive optimization of data processing workflows, query performance, and cost efficiency across Spark, Hadoop, and SQL-based systems.
• Data Governance: Establish data quality standards, lineage tracking, and governance frameworks ensuring regulatory compliance and data integrity.
• Collaboration: Partner with finance, accounting, risk, and operations teams to translate business requirements into robust data solutions.
• Team Development: Mentor and upskill engineers, fostering a strong engineering culture and building technical depth. Key Requirements:
• Experience: 5-8 years in data engineering with hands-on expertise in big data technologies; strong track record in banking/financial services middle office systems.
• Technical Expertise:
• Advanced proficiency in Apache Spark (Scala/Python)
• Expert-level SQL and relational database optimization
• Hadoop ecosystem experience (HDFS, MapReduce, Hive, HBase)
• Data pipeline orchestration tools (Airflow, Kubernetes, or equivalent)
• Domain Knowledge: Deep understanding of:
• Trade settlement and post-trade processing
• General ledger and financial accounting systems
• Regulatory reporting (CCAR, FRTB, SIMM, etc.)
• Middle office operations and reconciliation processes
• Cloud & DevOps: Experience with cloud platforms (AWS/GCP/Azure), containerization (Docker), and CI/CD pipelines.
• Leadership: Proven ability to lead and mentor data engineering teams, influence cross-functional stakeholders.
• Education: Bachelor's/Master's degree in Computer Science, Engineering, Data Science, or related field. Preferred Qualifications:
• Experience in tier-1 banks (Citigroup, Morgan Stanley, HSBC, JPMorgan, Goldman Sachs, Deutsche Bank, etc.)
• Background in financial accounting, general ledger reconciliation, or regulatory reporting systems
• Experience with distributed storage systems, data lakes, and modern data stack tools (Iceberg, Delta Lake, dbt)
• Knowledge of Python/Scala for data processing and automation
• Experience with streaming data platforms (Kafka, Flink, SparkStreaming)