Advanced Data Analyst

The interview process at Honeywell typically involves three rounds: a technical interview, a behavioral interview, and an HR interview. The technical interview will assess your skills in data analysis, visualization, and modeling, while the behavioral interview will assess your ability to work with stakeholders and communicate complex ideas. The HR interview will assess your fit with the company culture and values.

Honeywell has a diverse workforce of over 100,000 employees across the globe. The company has a strong presence in India and is committed to creating a work environment that is inclusive, diverse, and respectful. Honeywell provides its employees with a safe, healthy, and productive work environment and offers opportunities for professional growth and development.

Bachelor’s or Master’s Degree in Data Analytics, Computer Science, Engineering, or a related discipline; Strong experience in data analytics, reporting, or BI development; Experience working in a GBS/shared services environment is preferred; Proven track record of delivering end-to-end analytics solutions

Round 1: Technical Interview → Round 2: Behavioral Interview → Round 3: HR (based on company knowledge)

Job Title: Advanced Data Analyst Role Purpose: The Advanced Data Analyst is responsible for delivering high-quality analytics solutions that enable data-driven decision-making across the organization. This role combines technical expertise, business understanding, and stakeholder collaboration to design, develop, and support dashboards, reports, and data models. The role acts as a trusted analytics partner, ensuring solutions are aligned with business objectives, governed by strong data quality standards, and remain stable and scalable post deployment. Responsibilities Experience: Strong experience in data analytics, reporting, or BI development Experience working in a GBS/shared services environment is preferred Proven track record of delivering end-to-end analytics solutions Education: Bachelor’s or Master’s Degree in Data Analytics, Computer Science, Engineering, or a related discipline Key Responsibilities and Skills: Core Skill Proficiency Level Key Responsibilities Technical Skills AI Prompting Proficient Leverage AI to accelerate development and ensure high-quality, end-to-end delivery from development to deployment Familiarity with AI tools for analytics automation and solution development Data Analysis & Modeling Proficient Analyze and interpret data, generate insights, and support data-driven decision-making Strong SQL, data modeling techniques Data Visualization & Reporting Proficient Develop dashboards and reports to effectively communicate business insights Power BI Data Engineering & Transformation Proficient Prepare, clean, and transform data for analytics; build scalable datasets Data transformation techniques, understanding of data warehousing Data Quality & Governance Proficient Ensure accuracy, consistency, and reliability of data through validation and governance practices Data validation methods; data quality frameworks Stakeholder Management Proficient Engage stakeholders, gather requirements, and ensure alignment on deliverables and outcomes Communication and requirement-gathering tools/methods Process Improvement Proficient Identify inefficiencies and implement improvements to enhance analytics delivery Process optimization approaches, workflow tools Change Management Intermediate Support adoption of new solutions through stakeholder coordination and communication Change tracking and communication practices About Us Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable. Honeywell is a Fortune 100 company with a strong presence in India. The company has a diverse workforce of over 100,000 employees across the globe. With a rich history of innovation and a commitment to sustainability, Honeywell is a great place to start and grow your career. As a Data Analyst at Honeywell, you will have the opportunity to work on challenging projects, collaborate with cross-functional teams, and develop your skills in data analysis, visualization, and modeling. You will also have access to cutting-edge technology and tools, as well as opportunities for professional growth and development. Honeywell is committed to creating a work environment that is inclusive, diverse, and respectful. We believe that our employees are our greatest asset, and we strive to provide them with a safe, healthy, and productive work environment. In this role, you will be responsible for delivering high-quality analytics solutions that enable data-driven decision-making across the organization. You will work closely with stakeholders to gather requirements, develop dashboards and reports, and ensure that solutions are aligned with business objectives. You will also be responsible for ensuring the accuracy, consistency, and reliability of data through validation and governance practices. To be successful in this role, you will need to have strong experience in data analytics, reporting, or BI development, as well as experience working in a GBS/shared services environment. You will also need to have a proven track record of delivering end-to-end analytics solutions. Key Responsibilities and Skills: * Leverage AI to accelerate development and ensure high-quality, end-to-end delivery from development to deployment * Analyze and interpret data, generate insights, and support data-driven decision-making * Develop dashboards and reports to effectively communicate business insights * Prepare, clean, and transform data for analytics; build scalable datasets * Ensure accuracy, consistency, and reliability of data through validation and governance practices * Engage stakeholders, gather requirements, and ensure alignment on deliverables and outcomes * Identify inefficiencies and implement improvements to enhance analytics delivery * Support adoption of new solutions through stakeholder coordination and communication Technical Skills: * Familiarity with AI tools for analytics automation and solution development * Strong SQL, data modeling techniques * Power BI * Data transformation techniques, understanding of data warehousing * Data validation methods; data quality frameworks * Communication and requirement-gathering tools/methods * Process optimization approaches, workflow tools * Change tracking and communication practices Why Join This Company: Honeywell is a great place to start and grow your career. We offer a competitive salary and benefits package, as well as opportunities for professional growth and development. We are committed to creating a work environment that is inclusive, diverse, and respectful, and we strive to provide our employees with a safe, healthy, and productive work environment. As a Data Analyst at Honeywell, you will have the opportunity to work on challenging projects, collaborate with cross-functional teams, and develop your skills in data analysis, visualization, and modeling. You will also have access to cutting-edge technology and tools, as well as opportunities for professional growth and development. Growth Path: As a Data Analyst at Honeywell, you will have the opportunity to grow and develop your skills in data analysis, visualization, and modeling. You will work closely with stakeholders to gather requirements, develop dashboards and reports, and ensure that solutions are aligned with business objectives. You will also be responsible for ensuring the accuracy, consistency, and reliability of data through validation and governance practices. With experience and success in this role, you may have opportunities to move into more senior roles, such as Senior Data Analyst or Data Scientist. You may also have opportunities to work on more complex projects, collaborate with cross-functional teams, and develop your skills in data analysis, visualization, and modeling.