Job Description

Data Engineer with Capital Market Experience

Roles & Responsibilities

• Understanding of post-trade data flows including allocations, confirmations, settlement, risk, finance, and regulatory reporting.
• Knowledge of securities data modeling and financial data structures. Experience with reference data, security master data, and transactional trade data.
• Understanding of time-series data management and financial market data is a strong plus.
• Strong SQL development skills with experience designing and optimizing relational data models and database schemas.
• Proficiency in Python, including data processing frameworks such as Pandas and PySpark.
• Strong understanding of data warehouse, data lake, and Data Lakehouse concepts.
• Experience working with large-scale transactional and analytical data platforms.
• Experience with PostgreSQL, SQL Server, Snowflake, Redshift, Databricks, or similar database and data warehouse technologies on cloud, preferably AWS.
• Experience with stream and batch data processing technologies such as Kafka, Spark, Flink, or similar platforms.
• Experience building batch and streaming data pipelines, including ETL/ELT workflows, using Python and SQL.
• Strong understanding of data quality, data lineage, data validation, and reconciliation processes.
• Experience working with messaging technologies such as Kafka, RabbitMQ, IBM MQ, or similar platforms.
• Familiarity with monitoring and observability tools such as Datadog, Prometheus, and Grafana.
• Understanding of data security, privacy, and regulatory compliance requirements.
• Exposure to data science, machine learning, and AI/GenAI data preparation concepts is a plus.