Python Data Engineer with developing production - New York - Onsite - Locals only

Job Description:

Institutional Securities Technology team is looking for experienced Data Engineer with excellent knowledge of database and python for its Data Quality(DQ) and Client Confidentiality platform. The candidate will be working on design and development of our next generation applications in the above mentioned areas. Also the candidate will work with users to help onboard them on to the platform

Skills Required:

• Strong proficiency in Python with experience developing production-grade data processing pipelines.
• In-depth knowledge of database concepts, SQL queries, and stored procedures.
• Familiarity with various databases like DB2, Greenplum, Snowflake, PostgreSQL, KDB, and SingleStore.
• Expertise in Artifactory, Pandas, NumPy and object-oriented programming in Python.
• Strong data analytics skills and ability to identify data issues easily.
• Working knowledge of Unix and handling files in various formats like CSV and JSON.
• Experience with handling messages on Kafka.
• Knowledge of Git repositories, Jira tracking, and job scheduling tools like Autosys.
• Proficiency in writing unit tests (e.g., using pytest).
• Self-starter with the ability to work in a fast-paced environment and manage multiple projects.
• Finance data domain knowledge is preferred.

Good to Have:

• Working in some Data Quality related infrastructure
• Knowledge of anomaly detection algorithms and techniques, particularly isolation forest, clustering, time series analysis, and pattern mining
• Understanding of model performance monitoring, model debugging, and logging systems
• Some experience with containerization and deployment of ML services in enterprise environments