Description

Key Skills: Python, Oracle SQL, PL/SQL, AI Engineering, Data Engineering, ETL, Autosys, Unix/Linux, CI/CD, Kafka

Good to Have Skills: Experience with other database technologies like PostgreSQL and SQL Server. Familiarity with cloud platforms such as AWS, Azure, and GCP along with their data services. Knowledge of big data technologies including Spark and Hadoop. Demonstrated exposure to Agentic AI concepts, frameworks, and applications. Practical experience utilizing AI tools to improve productivity in data-related tasks such as code generation, anomaly detection, and automated data cleansing. Experience in developing and deploying machine learning models or AI solutions in production environments. Understanding of AI methodologies including Chunking, Embedding, Prompt Engineering.

Roles & Responsibilities:

• Design, develop, and optimize scalable and high-performance data pipelines using various technologies to support business intelligence and analytical needs.
• Work closely with business users, analysts, and other engineering teams to understand data requirements and translate them into technical solutions.
• Develop and maintain complex SQL and PL/SQL scripts for data extraction, transformation, and loading processes, primarily on Oracle databases, focusing on performance tuning and optimization.
• Implement and manage automation workflows using Autosys to schedule and monitor batch jobs, ensuring data availability and integrity.
• Develop and maintain data processing scripts and applications using Python, focusing on efficiency, reliability, writing performant code, and best practices.
• Manage and operate data processes within a Unix/Linux environment, including scripting for process automation, monitoring, and troubleshooting.
• Contribute to the continuous integration and continuous deployment pipeline for data solutions, promoting automation and efficiency in software delivery.
• Ensure data quality, accuracy, and consistency across all data platforms through comprehensive testing and validation processes.
• Explore, evaluate, and integrate Agentic AI frameworks and AI-driven tools to enhance productivity, automate routine tasks, and optimize data engineering workflows.
• Design, build, and deploy AI-driven solutions to solve complex business problems and enhance data analytics capabilities within the organization.
• Independently drive projects from inception to completion, taking ownership of technical design, implementation, and deployment while meeting business requirements.
• Provide technical guidance and mentorship to junior team members while fostering a collaborative and learning-oriented team environment.
• Act as a subject matter expert for data engineering practices and technologies within the team, staying current with industry trends.
• Troubleshoot data-related issues and perform root cause analysis to implement effective solutions that prevent future occurrences.

Experience Required: 10-15 years of progressive experience in Data Engineering roles within the finance industry with proven expertise in Oracle SQL and PL/SQL for complex data manipulation, stored procedures, functions, and database performance optimization.

Education: Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field

Key Skills

Education

Any Graduate