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About

Having decades of experience in Data Warehousing, Data modeling/Dimensional Modeling, BI/DW architecture, Database development projects for large Banking, Financial services and Insurance (BFSI) clients is an industry with extensive use of Microsoft SQL Server, T-SQL (SQL Server), Teradata, Hadoop, Python, PySpark, AWS, DevOps and UNIX technologies. •Have worked on various types of project such as Anti money Laundering (AML), Financial Analytics, Regulatory Reporting, Data Analytics , compliance, campaign data model & Data Migration. •Have worked on all aspects of project lifecycle such as design, architecting, development, integration, scheduling and supporting/maintenance. •Strong database, SQL, ETL and data analysis skills. •Expertise in Complex Query Analyzing, performance tuning and testing. •Experience in Data modeling using Ervin, SAP power designer to find, visualize, design, deploy and standardize high-quality enterprise data assets. •Stay current with industry trends, making recommendations as needed to help the clients excel. •Expertise in build ETL/ELT processes using SSIS, Azure Data Factory , Teradata SQL, AWS Cloud and Python, PySpark. •Expertise in Tableau & PowerBI to generate reports as per client requirements. •Worked on Job scheduling and orchestrating using Autosys, Airflow, BMC Control-M and Tivoli development activities.

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Skills

Experience

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Technology and Data Software Engineer

Artech L.L.C.

Oct-2024 to Present
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Data Engineer

Tata Consultancy Services(TCS), Texas

Aug-2022 to Oct-2024
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Data Engineer Lead

Beyondsoft Consulting Inc

Feb-2020 to Apr-2022
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Senior System Engineer

Beyondsoft Consulting Inc

Apr-2020 to Aug-2022
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Sr. Application consultant

Standard Chartered Bank

Jan-2016 to Feb-2020
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Technical Lead at DBS

DBS Bank

Sep-2015 to Jan-2016
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Technology Business Analyst

Standard Chartered Bank

Mar-2014 to Aug-2015
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Technical Lead

HCL Technologies Ltd

Jun-2011 to Feb-2014
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Senior system analyst

IBM India Private Limited

Mar-2010 to Jun-2011
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Senior Software Engineer

HCL Technologies Ltd

Nov-2008 to Mar-2010

Education

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Sri Venkateswara University, Tirupati (SVU)

B.Tech in Computer Science and Engineering

Passout Year: 2005

Publication

  • dott image May, 2024

Best Practices for End-to-End Data Pipeline Security in Cloud-Native Environments

Journal : CFSJ - Computer Fraud & Security Journal

Today, cloud-native data pipelines are a fundamental asset in data structures of present-day data-powered businesses, however, they present a major security risk through their full lifecycle...

  • dott image October, 2023

Architecting Aml Detection Pipelines Using Hadoop and Pyspark With AI/ML

As Financial Crimes Have Grown In Complexity, It Has Become Clear That Regular Rule-Based Aml Solutions Have Their Limits. It Describes A Pipeline Designed For Aml Detection Using Hadoop F...

  • dott image January, 2023

Case Study: Migrating Financial Data to AWS Red Shift and Athena

Journal : International Journal of Open Publication and Exploration

Today, financial institutions choose to move their financial data to the cloud so they can grow, gain access to analytics instantaneously and control costs. I analyze the adoption of Amazon ...

  • dott image October, 2022

Agile Delivery Models for Data-Driven UI Applications in Regulated Industries

Journal : A&M - Analysis and Metaphysics

This research study focuses on how to implement agile delivery model of data-driven user interface (UI) application within regulated industry. We explore the issues, approaches, and effectiv...

  • dott image February, 2022

OPTIMIZING TERADATA, HIVE SQL, AND PYSPARK FOR ENTERPRISE-SCALE FINANCIAL WORKLOADS WITH DISTRIBUTED AND PARALLEL COMPUTING

Journal : JoCAAA - Journal of Computational Analysis and Applications

Financial organizations deal with large amounts of information on transactions, markets and risks that must be sorted through rapidly and correctly. This research aims to discover how Terada...

  • dott image November, 2021

BUILDING COMPOSABLE MICROSERVICES FOR SCALABLE DATA-DRIVEN APPLICATIONS

Journal : International Journal of Communication Networks and Information Security

During the past decade, the rapid growth of data, rising user requirements and the need for stable applications have caused digital innovation to accelerate. Businesses that want to succeed ...

  • dott image December, 2020

Building Data Models for Regulatory Reporting in BFSI Using SAP Power Designer

Journal : IJSRSET - International Journal of Scientific Research in Science, Engineering and Technology

This paper explores how data modeling can improve the effectiveness and compliance of regulatory reporting in the BFSI sector using SAP PowerDesigner. Complying with regulations now requires...

Peer-Reviewed Articles

Leveraging Blockchain, Decentralized Identity (DID), and Social Integrations for Scalable, Trust-Centric Platforms: Composable Commerce in the Age of ...

This article examines how composable commerce architectures converge with Web3 technologies to transform digital commerce. Blockchain technology establishes transparent transaction frameworks that enhance trust through cryptographic verification rather than institutional guarantees. Decentralized identity specifications revolutionize authentication by returning data ownership to users while enhancing privacy through selective disclosure mechanisms. Social integrations create community-driven trust architectures that leverage token economics to align incentives between platforms and participants, enabling novel commercial interactions with minimal reliance on intermediaries. For organizations transitioning to Web3 commerce, layered architectural designs, progressive decentralization approaches, and robust security practices address the tensions between decentralization, security, and scalability. This technological convergence represents a fundamental restructuring of commercial relationships toward more equitable, transparent, and user-sovereign digital ecosystems.

Proven Patterns for Integrating Third-party Enrichments in Cloud-native Risk Scoring Engines

This article presents architectural patterns and implementation strategies for integrating third-party data enrichments into cloud-native risk scoring engines within the insurance technology domain. The transition to cloud-native architectures has fundamentally transformed how insurance carriers assess risk and deliver value. By implementing layered microservice architectures that separate enrichment processes from core risk calculation logic, insurance organizations achieve significant improvements in operational efficiency, development velocity, and underwriting precision. The article details a comprehensive framework for third-party data integration that incorporates API abstraction layers, event-driven processing, and standardized schemas. A critical component of this framework includes a robust data attribution and provenance tracking system that maintains visibility into data origins and transformation history, enabling enhanced regulatory compliance and systematic evaluation of data source value. Through a detailed case study of aerial imagery integration for roof condition assessment, the article demonstrates how high-resolution imagery processing techniques achieve remarkable accuracy in risk evaluation while reducing on-site inspection requirements. The implementation of flexible schema evolution strategies and asynchronous enrichment patterns further enables insurance platforms to accommodate continuous evolution in both internal models and external data sources. By documenting these proven integration patterns, the article contributes practical architectural approaches that balance performance, reliability, and maintainability while delivering measurable business outcomes across diverse regulatory and market contexts.

Real-Time Industrial Ecosystems: Advancing Predictive Maintenance and Smart Grid Optimization

This article examines the transformative impact of real-time industrial ecosystems on manufacturing and energy distribution sectors. By integrating Internet of Things (IoT) technologies, edge computing, and advanced analytics, these ecosystems enable unprecedented predictive capabilities and operational optimization. Edge-to-cloud architectures process time-sensitive data locally while leveraging cloud resources for complex analytics, creating unified data pipelines that integrate historical and streaming information. In manufacturing, predictive maintenance systems deploy strategic sensor networks to monitor equipment condition and detect anomalies before failures occur, extending equipment lifespan and reducing costs. Smart grid technologies revolutionize energy distribution through dynamic load balancing, renewable energy integration, and real-time pricing mechanisms that engage consumers as active participants. Looking forward, cross-sector synergies will emerge through data standardization, advanced artificial intelligence, and enhanced cybersecurity measures, creating increasingly autonomous industrial systems capable of self-optimization across multiple performance dimensions.

Personalized Learning Pathways: AI-Adaptive Educational Technology Supporting Diverse Learning Needs

This article explores the transformative potential of artificial intelligence in special education, addressing the persistent challenges faced by students with diverse learning needs. In the article of implementation studies across various educational contexts, we explore how AI-powered applications create personalized learning experiences through adaptive algorithms, cognitive assessment capabilities, and data-driven content customization. The article shows accessibility features including multi-modal content delivery, assistive technology integration, adaptive user interfaces, and real-time feedback mechanisms. Empirical evidence demonstrates significant improvements in academic outcomes, engagement levels, and cost-effectiveness compared to traditional interventions, with particularly strong effects in mathematics and reading comprehension. The article concludes with an examination of ethical considerations including data privacy, optimal technology-human instruction balance, emerging AI capabilities, and policy recommendations for equitable implementation, providing a framework for the development and deployment of AI-powered educational technologies for students with special needs.

Projects

Jan-1970 to Jan-1970

Policy management platform

Policy Management Technology (PMT) is a java based web application that was developed for the Policy Office (PO) team. PO team uses PMT to initiate, author and publish Enterprise and Business level policies, procedures and Guidelines. Published policies/procedures will be available in the Policy Library for team member’s reference. PMT is developed using Angular, Java and SQL Server 2019 technologies.
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Certificates

Issued : Nov 2021
  • dott image By : The Open Group
The Open Group Certified: TOGAF® 9 Certified
Issued : Mar 2019
  • dott image By : Scrum Alliance
Certified ScrumMaster (CSM)
Issued : Dec 2023
  • dott image By : Microsoft
Azure Fundamentals
Microsoft Certified: Azure Fundamentals

Membership

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Member

Association of Enterprise Architects

From year to

http://www.globalaea.org

Honours & Awards

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Editorial Board member
Awarded by:

International journal of scientific Research in computer science, Engineering and Information Technology

 Year: 2024

Scholar9 Profile ID

S9-062025-1114949

Publication
Publication

(7)

Review Request
Article Reviewed

(14)

Citations
Citations

(139)

Network
Network

(3)

Conferences
Conferences/Seminar

(0)

Academic Identity

Authors

Sukesh Reddy Kotha
Sukesh Reddy Kotha

Data Analytics Manag...
Manasa Talluri
Manasa Talluri

Principal Developer ...
Niranjan Reddy Rachamala
Niranjan Reddy Rachamala

Data Engineer Lead