Himansu Sekhar Patro Tumulu

• Collaborate with cross-functional teams to understand data requirements and design scalable and efficient data models.
• Develop and maintain data architecture, ensuring the integrity, reliability, and performance of data systems.
• Design, implement, and maintain ETL (Extract, Transform, Load) processes to move data from diverse sources to our data warehouse.
• Optimize and streamline data pipelines for maximum efficiency and performance.
• Implement and manage data warehouse solutions, ensuring they meet business requirements for performance and scalability.
• Monitor and maintain data warehouse health, troubleshooting and resolving issues as they arise.
• Integrate data from various sources to enable comprehensive analysis and reporting.
• Work with APIs and third-party integrations to enhance data sources and accuracy.
• Collaborate with data scientists to design and implement recommendation systems.
• Integrate machine learning models and algorithms into data pipelines to enhance user experience and engagement.
• Implement and enforce data quality standards and governance policies.
• Perform data profiling and validation to identify and rectify data quality issues.
• Collaborate with data scientists, analysts, and other stakeholders to understand and address their data-related needs.
• Provide technical support and guidance to the team on data-related matters.

Technical skills :

• Programming Languages: Proficiency in one or more programming languages commonly used in data engineering such as Python, Java, or others.
• Database Knowledge: Strong understanding of database technologies, including both relational databases (e.g., PostgreSQL, Snowflake ) and NoSQL databases (MongoDB).
• Machine Learning: Understanding of machine learning concepts and the ability to integrate machine learning models into data pipelines.
• ETL (Extract, Transform, Load): Experience in designing, implementing, and optimizing ETL processes to move and transform data between systems.
• Data Modeling: Ability to design and implement efficient and scalable data models to support business requirements.
• Data Warehousing: Experience in implementing and managing data warehouse solutions, including knowledge of data warehousing architectures and technologies.
• Big Data Technologies: Familiarity with big data frameworks and tools, such as Apache Hadoop, Apache Spark, or others.
• Cloud Platforms: Experience working with cloud platforms such as AWS.
• Version Control: Familiarity with version control systems (e.g., GitLab) for tracking changes in code and configurations.
• Data Governance: Understanding of data governance principles and the ability to implement and enforce data quality standards.
• Soft skills :
• Strong analytical and problem-solving skills to address complex data-related challenges.
• Time management skills
• Strong problem-solving skills and the ability to debug complex issues.
• Excellent communication and collaboration skills.
• Self-motivated and able to work independently as well as in a team.

• Researched and selected automation tools, prioritizing cost-effective solutions to shorten diagnostic workflows.
• Trained developers and quality assurance team members in automation programs and processes.
• Participated in test automation code review meetings and provided input on colleagues' coding efforts.
• Integrated test automation into layers of application stacks to improve product quality.
• Discussed requirements and processes with project managers and developers.
• Reviewed all test cases and test scripts for quality and identified additional areas to review.
• Completed automation of functional and regression testing.
• Applied Agile Delivery methods to simplify testing process decisions through iterative development.
• Implemented end-to-end automation and reducing test costs.

• Planned Agile best practices and encouraged team cohesion, overcoming impediments, and hurdles to productivity.
• Managed product backlog and supported Scrum framework for monthly sprint releases.
• Collaborated with product owners, team members, technologists, and other scrum masters to define solutions and drive progress.
• Facilitated Scrum framework – sprint planning, backlog grooming, daily scrums, sprint reviews, and sprint retrospectives.
• Coached teams in Agile practices and provided necessary training to create positive mindset to Agile methodologies.
• Applied agile methodology to shorten cycle time and achieve target margins.
• Led sprint reviews and planning meetings to promote full team engagement.

• Reduced project delivery time by implementing automated testing frameworks and tools.
• Advanced professional development by maintaining up-to-date knowledge of industry trends and advancements in software testing methodologies.
• Streamlined testing processes by developing reusable test scripts and templates.
• Optimized test coverage with risk-based analysis techniques, focusing on high-impact areas of the application.
• Partnered with business analysts to translate complex requirements into effective test cases.
• Participated in post-release reviews to analyze lessons learned from completed projects, driving process improvements for future endeavors.
• Collaborated with cross-functional teams to identify system requirements and develop effective test strategies.
• Enhanced product reliability through thorough functional, regression, and performance testing.