Data Engineer

Key Responsibilities Translate business requirement into queries against a set of relational tables and produce reporting based on the requirements. Design and build ETL pipeline from different data sources and act as a POC (Point of Contact) for user queries. Database and ETL development both on-prem and in cloud, including stored procedures, queries, performance tuning etc., using SQL and ETL tools. Create efficient testing automation script (using Python etc.) as part of the ETL or reconciliation process. Create BOXI (Business Objects) universes for self-service queries or build Tableau Dashboards for users metrics and KPIs. Build and improve DevOps pipeline and metrics. The current global team members are all very skilled in domain modeling, database design, big data, Java and cloud techniques so this is an excellent opportunity to play a key role in the growing team. Skills Required / Desired Strong scripting knowledge such as: Python and Shell. Strong relational database skills especially with DB2 / Snowflake. Create high quality and optimized stored procedures and queries. Strong with scripting language such as Python and Unix / K-Shell. Strong knowledge base of relational database performance and tuning such as: proper use of indices, database statistics / reorgs, de-normalization concepts. Experience on ETL processes and tools such as Informatica and Snowflake Spark / Databricks is a plus. Real time message processing experience is a big plus. Familiar with lifecycle of a trade and flows of data in an investment banking operation is a plus. Experienced in Agile development process. Java knowledge is a big plus but not essential. Experience in delivery of metrics / reporting in an enterprise environment (e.g. demonstrated experience in BI tools such as Business Objects, Tableau, report design & delivery) is a plus. Good team player; Integrity & ownership.