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Are you an expert in MS SQL Server & SSIS development who learned python and cloud engineering to stay ahead of the curve? We are seeking a lead data engineer to maintain and support our critical Pre-trade clearance system while working on re-engineering our entire data stack into AWS using python.
Job Responsibility:
Maintain and support our critical Pre-trade clearance system
Working on re-engineering our entire data stack into AWS using python
Requirements:
Deep expertise in Microsoft SQL Server, SSIS, and SQL development
Strong proficiency in writing and optimizing complex stored procedures, functions, and packages
Hands-on experience with Python for data manipulation, automation, and pipeline development
Familiarity with Oracle databases and PL/SQL development is required for cross-platform data integration
Experience in implementing CI/CD pipelines and DevOps practices for data solutions
Understanding data warehousing concepts, ETL methodologies, and data modeling techniques
Experience with Unix and Shell scripting
Experience with job scheduler tools such as BMC Control-M
Proven track record working in both waterfall and agile SDLC frameworks
Knowledge of the Financial Services industry including middle and back-office functions
Experience in collaborating with business counterparts to understand detailed requirements
Excellent verbal and written communication skills
Produce and maintain detailed technical documentation for all development efforts
Proficiency in additional programming/scripting languages, such as Python or PowerShell/Shell scripting
Familiarity with cloud platforms (e.g., Azure Data Factory, AWS Glue, Google Cloud)
Exposure to streaming technologies such as Kafka is a plus
Experience in financial services or enterprise-scale applications is preferred
Excellent communication, analytical, and problem-solving skills
Bachelor’s: Computer and Information Science (Required), High School (HS) (Required)
General Experience - 6 to 10 years
Nice to have:
Familiarity with cloud platforms (e.g., Azure Data Factory, AWS Glue, Google Cloud) and experience implementing CI/CD pipelines and DevOps practices for data solutions is a strong advantage
Exposure to streaming technologies such as Kafka is a plus
Experience in financial services or enterprise-scale applications is preferred