6 Subsetting Jobs

Job Description Ford Credit's Tech Team in India is actively seeking a highly skilled and experienced Senior Test Data Management Engineer to join our team. In this crucial role, you will be responsible for defining, implementing, and managing test data strategies and solutions specifically for our complex financial applications. Leveraging your deep expertise with IBM Optim, you will ensure that our testing environments are populated with realistic, compliant, and high-quality data, enabling robust and efficient testing across various phases. You'll play a key role in safeguarding sensitive financial data through effective masking and subsetting techniques while supporting our development and QA teams This is a senior-level position requiring deep technical expertise, strategic thinking, and the ability to mentor others and drive TDM excellence throughout the organization. Responsibilities Test Data Management Engineer - Role & Responsibilities : TDM Strategy & Design: Define, develop, and implement comprehensive Test Data Management (TDM) strategies, frameworks, and processes tailored for financial applications. Analyze complex application data models and relationships to design effective data subsetting, masking, and generation solutions using IBM Optim. Collaborate with stakeholders (QA, Development, Business Analysts, Compliance) to understand test data requirements and translate them into technical TDM solutions. TDM Solution Implementation & Management: Design, configure, and execute TDM processes using relevant TDM tools (subsetting, masking, generation, synthetic data creation, data refresh). Implement and manage data masking/obfuscation techniques to comply with data privacy regulations (e.g., GDPR, CCPA, etc.) and internal policies for sensitive financial data. Manage the lifecycle of test data environments, including planning refresh cycles, executing data provisioning requests, and managing data retention. Troubleshoot and resolve complex test data-related issues across different environments. Data Analysis & Provisioning: Perform in-depth data analysis to identify critical data elements, sensitive data, and complex data relationships required for various testing cycles (functional, performance, UAT). Provision timely and relevant test data sets to different testing environments based on project needs. Troubleshoot and resolve test data-related issues, ensuring data integrity and quality. Compliance & Security: Ensure all TDM activities adhere strictly to internal data governance policies and external financial regulations regarding data privacy and security. Work closely with Compliance, Security, and Audit teams to validate TDM processes and controls. Performance & Automation: Optimize IBM Optim processes and underlying database interactions for performance and efficiency. Identify opportunities for automation in test data provisioning and management workflows. Collaboration & Business Alignment: Establish and promote TDM best practices, standards, and guidelines across the organization. Create and maintain detailed documentation for TDM processes, tools, and environments. Work closely with Database Administrators (DBAs) to manage test data storage, performance, and access. Collaborate with DevOps engineers to integrate TDM processes into CI/CD pipelines where applicable. Collaborate closely with Product Owners, Business Analysts, Software Engineers, to understand complex financial requirements, define precise testing criteria, and prioritize automation efforts. Qualifications Must Have: 10+ years of overall experience in IT, with a strong focus on Quality Assurance, Data Management, or Software Engineering. 6+ years of dedicated experience in Test Data Management (TDM). Proven experience implementing and managing TDM solutions for complex enterprise applications, preferably in the financial services industry. Strong Hands-on experience with industry-standard TDM tools like IBM Optim and Opensource tools Experience working in highly regulated environments with a strong understanding of data privacy and compliance challenges in finance. Strong SQL skills and experience working with various relational databases (e.g., Oracle, SQL Server, DB2, PostgreSQL , BQ, etc). Solid understanding of data modeling concepts and database structures. Proficiency in data masking, subsetting, and synthetic data generation techniques. Experience with scripting languages (e.g., Python, Shell, Perl) for automation and data manipulation. Experience with RBAC and have worked with Infra teams to achieve CI/CD automation to produce masked test data from production on demand. Familiarity with Linux/Unix command line. Solid understanding of data refreshers process Solid understanding of financial industry data structures, workflows, and testing challenges (e.g., trading, payments, banking, accounting, regulatory reporting). In-depth knowledge of relevant data privacy regulations (e.g., GDPR, CCPA, etc.) and their impact on test data handling. Excellent analytical and problem-solving skills with the ability to tackle complex data challenges. Strong communication and interpersonal skills, with the ability to explain technical concepts to non-technical stakeholders. Must have experience working with US public companies, with a strong understanding of security processes and how to apply them to Test Data Management (TDM) to ensure compliance with regulations. Ability to work effectively both independently and as a leader or contributor within a team. Proven ability to mentor junior team members and drive adoption of best practices. Nice to Have: Experience with specific TDM tools like, Informatica TDM, Alteryx , PyETL,Deequ, Google DVT, etc Experience with data virtualization tools. Experience with AI for Synthetic Data Generation. Experience with cloud platforms (AWS, Azure, GCP) and cloud database services. Experience integrating TDM processes into CI/CD pipelines. Familiarity with performance testing concepts and data needs. Relevant certifications in TDM, databases, or cloud technologies. Preferred Qualification: Bachelor’s Degree in Computer Science, Engineering or equivalent work experience Min of 6+ Test Data Management Engineer Show more Show less

Job Description for TDM Engineer: Location : Hyderabad Experience : 3 to 5Years Notice Period : Immediate to 30days Test Data Management (TDM) Engineer: We are urgently looking for a hands-on Test Data Management (TDM) Engineer with 3–5 years of experience (slightly higher experience can also be considered). The ideal candidate should be a self-starter , possess strong communication skills , and be capable of independently driving TDM implementation efforts. Key Responsibilities: Work within the Enterprise Platform Enablement team to implement high-performing Test Data Management solutions . Understand and address Data Masking and Test Data needs of distributed and mainframe application teams . Take ownership of the architecture, design, development, testing, and support of TDM implementations. Collaborate with application owners to analyze data privacy requirements and deliver TDM strategies accordingly. Required Skills: Hands-on experience with TDM tools (e.g., Informatica TDM, Delphix, IBM Optim, CA TDM, etc.). Good knowledge of data masking, subsetting, synthetic data generation , and data provisioning strategies. Understanding of data privacy and compliance practices. Exposure to enterprise environments (including Mainframe and Distributed Systems ). Strong problem-solving skills and the ability to communicate effectively across technical and business stakeholders. Able to work independently , manage priorities, and meet deadlines under pressure. About Novastrid: NOVASTRID is a be spoke Mobile App and Web Development Company with a User-Centric approach to product development servicing Start-ups, SMEs & Enterprises across the world Our deep skill stack straddles both technology and business helping clients materialize their ideas and business process to reality with 0% user friction at the last mile. Show more Show less

Summary Position Summary Associate Vice President - Quality Engineer Specialist (AI) Role Overview: As a Quality Engineer Specialist Leader specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft and be the visionary driving force behind our transformation to AI-powered quality engineering, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while driving tangible value for Deloitte's business investments. Leveraging your extensive quality engineering and AI craftsmanship, along with advanced proficiency across multiple quality assurance disciplines and modern AI/GenAI frameworks and models, you will consistently demonstrate an exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a strong background in quality assurance, test automation, and a deep understanding of AI and GenAI technologies, including their application to quality engineering. This role is crucial in enhancing our testing frameworks and ensuring the highest quality standards for our products. The team US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Responsibilities: Strategic Vision and Alignment: Accountable for crafting and articulating a vision for AI/GenAI as it specifically applies to quality engineering in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams across various organizational levels. Advocacy and Technology Roadmap: Advocate for, develop, and communicate the AI/GenAI quality engineering implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress. Focus on reuse and leverage of existing quality assets to minimize overall costs with an eye on continuous improvement. Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs related to quality approaches, automation tools, test data management (e.g., subsetting, masking, generation, virtualization, anonymization), and standards, ensuring they are fit-for-purpose in product testing cycles. Implement advanced techniques such as BDD and GenAI-based automation to evolve testing frameworks and increase automation coverage, minimizing manual quality assurance to exceptional scenarios only. Establish and refine AI/ML/GenAI domain standards and best practices. Remain hands-on with test design and scripting/coding automations, contributing to team velocity during sprints, and actively engage with engineers across the SSDLC. Be self-driven to learn new technologies, experiment with them, and inspire quality engineers to apply new technologies effectively. Capability Evolution and Development: Mentor and develop quality engineers to become masters of their craft. Coach and develop their skills in modern engineering practices, specifically related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations with academia and communities. Iterative Value Delivery: Embrace an iterative/incremental approach to quality engineering. Apply a leaning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence. Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement. Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering and quality engineering practices. Identify inefficiencies and opportunities for innovation. Act as a role model and enhance the product engineering operating model to be lean, adaptable, and responsive to changes, ensuring that quality engineering teams can deliver business value efficiently and effectively. Guide and transform the organization to embrace lean principles and foster a culture of innovation. Tech/Quality Risk Management: Ensure appropriate quality tool use, adoption by quality engineers, and confirm/review that products are tested, scaled, and operated to be free of defects and are secure/compliant, including providing guidance for necessary optimizations. Identify potential quality risks and develop mitigation strategies. This involves proactive problem-solving and contingency planning to address any issues that may arise during development. Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence. Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization, from team members to middle management to executives. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels. Key Qualifications: A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 15+ years of hands-on experience in quality assurance/engineering, test automation including coding the test scripts, and in AI/ML, with last 2 years focused on GenAI as well. Proven experience in Python, TensorFlow, PyTorch, Keras, C#, Julia, and ML libraries. Strong experience in GenAI models and technologies such as OpenAI, Claude, Gemini, LangChain, Vector databases, and approaches like prompt engineering, fine-tuning, etc. Hands-on experience with automation-first techniques like BDD and test automation tools such as TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ. Strong experience with cloud hyper-scalers like AWS, Azure, and GCP. Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, and deployment techniques like Blue-Green, and Canary to enable A/B testing approaches. Proven track record of leading and managing high-performing quality engineering teams. Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 302376 Show more Show less

Summary Position Summary Associate Vice President - Quality Engineer Specialist (AI) Role Overview: As a Quality Engineer Specialist Leader specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft and be the visionary driving force behind our transformation to AI-powered quality engineering, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while driving tangible value for Deloitte's business investments. Leveraging your extensive quality engineering and AI craftsmanship, along with advanced proficiency across multiple quality assurance disciplines and modern AI/GenAI frameworks and models, you will consistently demonstrate an exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a strong background in quality assurance, test automation, and a deep understanding of AI and GenAI technologies, including their application to quality engineering. This role is crucial in enhancing our testing frameworks and ensuring the highest quality standards for our products. The team US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Responsibilities: Strategic Vision and Alignment: Accountable for crafting and articulating a vision for AI/GenAI as it specifically applies to quality engineering in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams across various organizational levels. Advocacy and Technology Roadmap: Advocate for, develop, and communicate the AI/GenAI quality engineering implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress. Focus on reuse and leverage of existing quality assets to minimize overall costs with an eye on continuous improvement. Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs related to quality approaches, automation tools, test data management (e.g., subsetting, masking, generation, virtualization, anonymization), and standards, ensuring they are fit-for-purpose in product testing cycles. Implement advanced techniques such as BDD and GenAI-based automation to evolve testing frameworks and increase automation coverage, minimizing manual quality assurance to exceptional scenarios only. Establish and refine AI/ML/GenAI domain standards and best practices. Remain hands-on with test design and scripting/coding automations, contributing to team velocity during sprints, and actively engage with engineers across the SSDLC. Be self-driven to learn new technologies, experiment with them, and inspire quality engineers to apply new technologies effectively. Capability Evolution and Development: Mentor and develop quality engineers to become masters of their craft. Coach and develop their skills in modern engineering practices, specifically related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations with academia and communities. Iterative Value Delivery: Embrace an iterative/incremental approach to quality engineering. Apply a leaning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence. Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement. Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering and quality engineering practices. Identify inefficiencies and opportunities for innovation. Act as a role model and enhance the product engineering operating model to be lean, adaptable, and responsive to changes, ensuring that quality engineering teams can deliver business value efficiently and effectively. Guide and transform the organization to embrace lean principles and foster a culture of innovation. Tech/Quality Risk Management: Ensure appropriate quality tool use, adoption by quality engineers, and confirm/review that products are tested, scaled, and operated to be free of defects and are secure/compliant, including providing guidance for necessary optimizations. Identify potential quality risks and develop mitigation strategies. This involves proactive problem-solving and contingency planning to address any issues that may arise during development. Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence. Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization, from team members to middle management to executives. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels. Key Qualifications: A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 15+ years of hands-on experience in quality assurance/engineering, test automation including coding the test scripts, and in AI/ML, with last 2 years focused on GenAI as well. Proven experience in Python, TensorFlow, PyTorch, Keras, C#, Julia, and ML libraries. Strong experience in GenAI models and technologies such as OpenAI, Claude, Gemini, LangChain, Vector databases, and approaches like prompt engineering, fine-tuning, etc. Hands-on experience with automation-first techniques like BDD and test automation tools such as TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ. Strong experience with cloud hyper-scalers like AWS, Azure, and GCP. Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, and deployment techniques like Blue-Green, and Canary to enable A/B testing approaches. Proven track record of leading and managing high-performing quality engineering teams. Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 302376 Show more Show less

Experience: 3–5 years (Candidates with slightly higher experience can also be considered) Location: Hyderabad Urgency: Immediate requirement We are urgently looking for a skilled and proactive Test Data Management (TDM) Engineer to join our Enterprise Platform Enablement team. The ideal candidate must be a self-starter with excellent communication skills and hands-on experience in implementing high-performing TDM solutions. This role involves working closely with application teams to understand and fulfill data masking and test data provisioning needs across distributed and mainframe environments. Roles and Responsibilities: Design, implement, and maintain Test Data Management solutions across enterprise systems. Collaborate with application teams to gather requirements for data masking and test data provisioning. Build and support TDM architecture for both Distributed and Mainframe environments. Perform data subsetting, data masking, data cloning, and synthetic data generation. Conduct unit testing, integration testing, and support QA activities. Troubleshoot TDM-related issues and ensure data privacy compliance. Maintain technical documentation and support governance and audit processes. Mandatory Skills: 3–5 years of hands-on experience in Test Data Management (TDM) . Strong experience with TDM tools like Informatica TDM , CA Test Data Manager , Delphix , or similar platforms. Proven expertise in Data Masking , Data Subsetting , and Synthetic Data Generation . Experience working with Relational Databases (Oracle, SQL Server, DB2, etc.) . Familiarity with mainframe data systems (e.g., DB2 z/OS, VSAM) . Proficient in SQL , PL/SQL , and scripting for automation (e.g., Shell, Python). Good understanding of data privacy regulations (e.g., GDPR, HIPAA). Excellent analytical, problem-solving, and communication skills. Ability to work independently and manage multiple priorities effectively. Preferred Skills: Exposure to Agile/Scrum methodologies. Knowledge of CI/CD pipelines and integration with DevOps tools. Experience in enterprise-level software development and deployment practices. Show more Show less

Role Overview:Test Automation Practice Lead with 8–12 years of experience in Mumbai's banking/fintech domain. The ideal candidate will demonstrate expertise in designing and implementing advanced test automation frameworks and possess deep technical knowledge in tools and techniques specific to the banking/fintech sector. This role involves leading test automation initiatives, working collaboratively with cross-functional teams, and driving innovation to enhance quality assurance processes. Key Responsibilities: 1. Strategic Leadership: o Define, develop, and execute test automation strategies tailored to the banking/fintech domain. o Lead automation efforts across diverse banking products, including Loan Management Systems, Core Banking Products, Internet Banking, and Mobile Banking platforms. o Champion in-sprint automation and ensure seamless integration with DevOps CI/CD pipelines. 2. Framework Development: o Design and implement various test automation frameworks, including: ▪ Page Object Model (POM). ▪ Keyword/Action Word Frameworks. ▪ Data-Driven and Hybrid Frameworks. ▪ Image-Based Frameworks (e.g., Sikuli, Eggplant TestPlant). o Develop scalable and maintainable frameworks that align with project requirements. 3. Technical Expertise: o Apply advanced skills in Core Java for framework and script development. o Utilize tools such as Selenium, Appium, TOSCA, and API testing tools like RestAssured, Postman/Newman, and Insomnia. o Leverage service virtualization tools (e.g., Parasoft Virtualize, CA DevTest, Microfocus Virtualize, Tricentis Virtualize, Hoverfly) for complex test scenarios. 4. Data Management: o Implement test data management solutions, including: ▪ Data subsetting at source. ▪ Data masking techniques. ▪ Creating islands of data without referential integrity issues. 5. Team Collaboration: o Partner with development, product, and QA teams to ensure the integration of test automation into all stages of the development lifecycle. o Mentor and train team members to enhance their technical expertise and efficiency. 6. Process Optimization: o Drive continuous improvement initiatives in test automation and quality assurance processes. o Optimize API integration testing for 3rd-party products and services. Required Skills & Expertise: • Strong proficiency in Core Java. • Expertise in test automation tools like Selenium, Appium, TOSCA, and other similar products. • Extensive experience in API testing using RestAssured, Postman/Newman, or Insomnia. • Proficiency in designing various automation frameworks (POM, Keyword/Action Word, Data Driven, Hybrid, Image-Based). • Hands-on experience in service virtualization and tools such as Parasoft Virtualize, CA DevTest, Tricentis Virtualize, etc. • Solid knowledge of test data management, including subsetting, masking, and data preparation techniques. • Familiarity with DevOps practices and tools for CI/CD integration. AVEKSHAA TECHNOLGIES (P) LTD. TEST AUTOMATION PRACTICE LEAD • Domain expertise in banking/fintech products and services. Qualifications: • Bachelor’s/Master’s degree in Computer Science, Information Technology, or a related field. • 8–12 years of relevant experience in test automation with significant exposure to the banking/fintech domain. • Hands-on experience with modern automation and virtualization tools. • Strong understanding of quality assurance processes and methodologies. For additional details, please visit www.avekshaa.com Interested, please share your profile with piyali.das@avekshaa.com