Sravantesh Neogi

Dynamic software engineering leader with a proven track record of driving impactful results through strategic team management and technical expertise. Extensive experience in software development, project management, and cross-functional collaboration, complemented by a strong foundation in agile methodologies and performance optimization. Recognized for adaptability and fostering innovation within fast-paced environments while maintaining a focus on quality assurance and compliance with industry standards. Committed to enhancing team collaboration and delivering high-quality outcomes by leveraging skills in test automation, manual testing, and proactive problem-solving to identify inefficiencies and implement continuous improvements.

• Attention Mechanism

Automated Metrics data Collection using Power Automate

08/2024 - Present

Lexmark

This project was initiated to address the growing need for real-time visibility into software qualitymetrics across multiple QA teams and projects. Traditionally, tracking key quality indicators such asdefect counts, fix rates, breakage percentages, and DRE (Defect Removal Efficiency) was a manual,fragmented process—often relying on spreadsheets, inconsistent reporting formats, and delayedupdates. To streamline this, I designed and implemented an automated, end-to-end reportingsolution that leverages Azure DevOps OData feeds and Power BI to extract, process, and visualizequality metrics in a centralized dashboard.Some key objectives ibcluded elimination of manual effortin collecting and consolidating QA metrics,providing real-time, accurate insights into test and defecttrends,enabling data-driven decision-making for QA leadership and stakeholders and promotion ofshift-left testing visibility by tracking early-phase test executions.•

Power BI Dashboard for Automation Execution Details

08/2024 - Present

In our organization, various QA teams employed different automation execution strategies and reliedon diverse scheduling mechanisms such as cron jobs, Jenkins pipelines, and Azure DevOps (ADO)pipelines. This lack of standardization made it increasingly difficult for senior management to gain aunified view of the overall health, status, and effectiveness of our automation efforts. To address thischallenge, I conceptualized and implemented a centralized monitoring and reporting solution usingMicrosoft Power Automate and Power BI. The solution was designed to aggregate execution datafrom multiple sources, including: Email-based test reports ,Azure DevOps pipeline logs, Jenkins joboutputs, Other custom automation triggers Using Power Automate, I built workflows to extract and•

normalize data from these disparate sources. This data was then fed into a Power BI dashboard,which provided real-time, visual insights into: Execution success/failure rates ,Test coverage trends,Pipeline performance metrics and Historical comparisons and alerts .This solution significantlyimproved transparency and decision-making for leadership by offering a single-pane-of-glass viewinto the QA automation landscape. It also reduced manual reporting efforts and enabled proactiveissue identification across teams.

Lexmark Let'sLearn Program

The LetsLearn Programme is a comprehensive, organization-wide initiative designed to serve as acentralized platform for all technical and people-focused learning needs. It aims to foster a culture ofcontinuous learning, upskilling, and leadership development across geographically distributed teams,with a special focus on the Software Products (SW Products) area in India and Cebu. The main visionof this project is to empower employees with the knowledge, skills, and mindset required to thrive in adynamic technology landscape—by offering accessible, relevant, and high-impact learningexperiences. I was part of the 2 member governing team to visualised and conceptualised thisprogram.

Cloud Authentication using Face Recognition as a 2FA

As part of the Lexmark F2F event in 2020, I worked on the project which aimed to enhance the securityof cloud-based systems by integrating facial recognition technology as a second factor ofauthentication (2FA). Traditional 2FA methods, such as SMS codes or authenticator apps, whileeffective, can be susceptible to phishing, SIM swapping, or device compromise. To address thesevulnerabilities, the project introduced a biometric layer that leverages the uniqueness of facialfeatures to verify user identity. The solution was designed to work seamlessly with existing cloudauthentication workflows. Upon successful entry of primary credentials (username and password),users are prompted to undergo a real-time facial scan using their device’s camera. The capturedimage is then matched against a securely stored facial template using advanced computer visionand machine learning algorithms. Key components of the project included: Face detection andrecognition engine using OpenCV and deep learning models. Secure facial data storage andencryption compliant with privacy standards. Integration with cloud identity providers for seamlessauthentication flow.

SAP Device Types Automation

Lexmark has traditionally provided SAP device types—configuration files that enable customers usingSAP systems to print seamlessly to Lexmark printers. These device types were manually designed,developed, and tested by engineers before being published on the SAP platform. To facilitate this,Lexmark maintained a Gold Partnership with SAP, which allowed developers to remotely access SAPworkstations located in Germany. This setup was essential, as the creation and validation of thesedevice types had to be performed directly within SAP environments. However, the entire process wasmanual, time-consuming, and error-prone, typically requiring 5 to 6 days to complete a single devicetype from start to finish. To address this inefficiency, I developed a suite of automation scripts thatstreamlined the end-to-end process—from design and development to testing. With this automationin place, the overall effort was reduced by approximately 85%, bringing the total time down to just 5 to6 hours. This not only accelerated delivery but also significantly improved consistency and reducedthe likelihood of human error.

Languages : Hindi, English and Bengali

Hobbies: Travelling, reading, cooking

• Manager Appreciation Award
• 2025-01 Lexmark International India, Manager Appreciation Award
• 2022-08 Lexmark International, Judges Critics Award – Lexmark India Focus To Future
• 2020-10 Lexmark, Manager Appreciation Award
• 2015-08 Lexmark International, Lexmark Make It Happen
• 2013-05 Lexmark International

Travelling, Reading, Cooking