Business Analyst - Manufacturing Domain (5-7 yrs)

Business Analyst

Key Responsibilities :

- Engage with stakeholders to thoroughly understand business requirements, translating them into actionable data analytics solutions that align with strategic goals.

- Conduct in-depth analysis to gather and document detailed business and technical requirements for various data analytics projects, ensuring clarity and precision in all documentation.

- Examine and interpret data to identify actionable trends, patterns, and insights that can drive informed business decisions and strategies.

- Collaborate closely with data engineers and data scientists to ensure the accurate and effective implementation of data solutions that meet business objectives.

- Develop, update, and maintain comprehensive documentation related to data analytics processes, systems, and procedures, ensuring accessibility and consistency.

- Facilitate seamless communication and coordination between business units and technical teams, fostering a collaborative environment that enhances project outcomes.

- Support the testing and validation phases of data analytics solutions, ensuring their efficacy and alignment with specified requirements.

- Ensure the highest standards of data quality and integrity across all data analytics initiatives, implementing best practices and continuous improvement measures.

- Create compelling visualizations and reports to effectively communicate insights to stakeholders, enabling data-driven decision-making processes.

- Stay abreast of industry trends, emerging technologies, and best practices in data analytics and business analysis, continuously enhancing your skill set and knowledge base.

- Assist in the development and implementation of data governance policies and procedures to ensure responsible data management and compliance with regulatory standards.

- Act as a liaison between the business and technical teams to ensure alignment and mutual understanding of project goals, timelines, and deliverables.

- Provide training and support to team members and stakeholders on data analytics tools, methodologies, and best practices to promote data literacy and self-service analytics.

Qualifications :

- Bachelor's degree in business, Computer Science, Information Technology, or a related field, providing a solid foundation for analytical and technical expertise.

- At least 5 years of experience as a Business Analyst, ideally within the Data Analytics,

- Manufacturing or Procurement domains, showing a proven record of accomplishment of successful project delivery.

- Exceptional analytical and problem-solving skills, with the ability to dissect complex data sets and identify meaningful patterns and insights.

- Proficiency in data analysis tools and techniques, including SQL, data visualization tools (e., Tableau, Power BI), and statistical software, enabling comprehensive data evaluation and presentation.

- Outstanding written and verbal communication skills, facilitating clear and effective interactions with stakeholders at all levels.

- Ability to work independently while also thriving in a collaborative team environment, demonstrating flexibility and adaptability.

- Strong organizational and project management skills, ensuring timely and efficient completion of tasks and projects.

- Keen attention to detail and a steadfast commitment to maintaining data quality and accuracy in all deliverables.

- Knowledge and experience with Manufacturing and Procurement processes and systems are highly desirable, adding value to our data analytics initiatives.

- Experience with Agile methodology and project management tools such as JIRA, Devops or Trello is required, contributing to efficient and organized project workflows.

- Strong understanding of data governance principles and practices, ensuring compliance with data privacy regulations and maintaining data integrity.

- Demonstrated ability to develop and deliver effective presentations and training sessions to diverse audiences, enhancing data literacy and fostering a culture of data-driven decision- making