Prasada Tammisetty

18 years of experience primarily in Banking and Financial Services, with strong expertise in FR 2052a FED Regulatory Reporting (5G & 6G), Analytics, and Data Governance. Proven track record in the design, development, and implementation of Cloud Data Lake, Data Mesh, Data Warehouse, and Business Intelligence solutions. Possesses strong technical, analytical, and functional skills, with end-to-end ownership across SDLC and Agile methodologies, including requirements analysis, documentation, architecture design, development, testing, implementation, production support, incident management, root cause analysis, and real-time debugging. Designed and delivered cloud-native solutions with a strong focus on engineering excellence, automation, innovation, and cross-team collaboration. Continuously evaluated and adopted new technologies, tools, and working practices, demonstrating agility and a strong learning mindset. Brought a curious, questioning approach to solution design, contributing innovative ideas and improving architectural and operational outcomes. Triaged complex production issues, performed root cause analysis (RCA), and made decisive, data-driven decisions under high-pressure scenarios. Acted confidently in break-glass production incidents, restoring services and minimizing customer impact during critical outages. Designed and implemented scalable solutions using AWS services, including compute, storage, networking, containers, and serverless frameworks. Built and deployed applications using Infrastructure as Code (IaC) tools such as Cloud Formation, Terraform, Ansible, and ARM, ensuring repeatability and compliance. Applied object-oriented principles and design patterns to develop maintainable, extensible, and high-performing applications. Developed and deployed containerized applications, leveraging Docker and Kubernetes, with strong experience deploying workloads on Amazon EKS. Implemented CI/CD pipelines using Jenkins and Git-based workflows, enabling automated build, test, and deployment processes. Collaborated effectively with distributed teams and stakeholders, both in-person and virtually, building trusted and productive working relationships. Worked with enterprise database technologies including Oracle, PostgreSQL, and SQL Server to support transactional and analytical workloads. Defined and implemented cloud reliability, resiliency, and observability strategies, ensuring high availability and performance of Tier-3 critical systems. Established and enforced engineering standards and best practices, contributing to increased engineering maturity and operational stability. Deployed and managed LLM-based solutions, including Retrieval Augmented Generation (RAG) architectures in cloud environments. Built full-stack AI-powered applications, integrating LLMs with backend services and cloud infrastructure. Applied best practices in prompt engineering, data privacy, hallucination mitigation, bias awareness, token usage, and cost optimization. Demonstrated understanding of GenAI modalities, determinism vs. randomness, and agentic behavior in production systems. Developed AI workflows and services using object-oriented Python, ensuring scalability, reliability, and maintainability. Data engineering professional poised to add significant value through comprehensive experience in developing scalable data solutions. Noted for strong team collaboration and adaptability in fast-paced environments. Reliable in driving results with key skills in data modeling, ETL processes, and cloud-based data platforms. Experienced with building and maintaining data pipelines to ensure seamless data flow. Utilizes advanced knowledge of big data technologies to drive data-driven decision-making. Track record of enhancing data architecture for improved performance and reliability. Senior engineering professional with deep expertise in data architecture, pipeline development, and big data technologies. Proven track record in optimizing data workflows, enhancing system efficiency, and driving business intelligence initiatives. Strong collaborator, adaptable to evolving project demands, with focus on delivering impactful results through teamwork and innovation. Skilled in SQL, Python, Spark, and cloud platforms, with strategic approach to data management and problem-solving. Diligent [Desired Position] with robust background in data engineering and proven ability to design and implement complex data pipelines. Successfully contributed to optimizing data architecture and enhancing data processing efficiencies. Demonstrated expertise in big data technologies and proficiency in Python and SQL. Responsive expert experienced in monitoring database performance, troubleshooting issues and optimizing database environment. Possesses strong analytical skills, excellent problem-solving abilities, and deep understanding of database technologies and systems. Equally confident working independently and collaboratively as needed and utilizing excellent communication skills. Detail-oriented [Job Title] designs, develops and maintains highly scalable, secure and reliable data structures. Accustomed to working closely with system architects, software architects and design analysts to understand business or industry requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design and implementation stages. Astute [Job Title] with data-driven and technology-focused approach. Communicates clearly with stakeholders and builds consensus around well-founded models. Talented in writing applications and reformulating models.

• Google Cloud Certified – Professional Cloud Architect
• Certified Pega System Architect.
• Oracle Certified Associate OBIEE
• C and C++ - Electronics Corporation of India Limited