Data Analyst Role

Candidates typically face a timed online aptitude test followed by a technical interview focused on SQL, Power BI, and data‑modeling scenarios. The HR round assesses cultural fit and communication skills. Overall difficulty is moderate, with emphasis on practical analytics knowledge and clear problem‑solving articulation.

CAES by Honeywell fosters a collaborative and inclusive environment where engineers and analysts work on high‑impact projects. Employees enjoy a balance of challenging assignments and supportive mentorship, with ample opportunities for upskilling and internal mobility.

Bachelor’s or Master’s degree in Data Analytics, Computer Science, Engineering or related discipline; minimum 60% aggregate (or CGPA 6.0/10); final year students of 2025/2026 batches eligible; no active backlogs at the time of joining; strong analytical mindset and communication skills.

Round 1: Online aptitude & logical reasoning test → Round 2: Technical interview covering SQL, Power BI, data modeling and AI prompting → Round 3: HR interview focusing cultural fit and career aspirations

Honeywell is a global technology leader that helps organizations solve complex challenges across aerospace, building automation, energy, safety and industrial automation. Through its Honeywell Forge platform, the company delivers data‑driven solutions that make operations smarter, safer and more sustainable. CAES (Honeywell Connected Enterprise Solutions) is the business unit that brings together analytics, IoT, and cloud capabilities to enable digital transformation for customers worldwide. Working at CAES offers exposure to cutting‑edge technologies, cross‑functional collaboration, and a culture that values innovation, continuous learning, and ethical engineering. The Advanced Data Analyst role is a pivotal analytics partnership position within CAES. The analyst will translate business problems into data solutions, build end‑to‑end reporting pipelines, and ensure the reliability and scalability of analytics deliverables. Acting as a trusted advisor, the analyst will collaborate with functional heads, GBS teams, and technology partners to drive data‑centric decision making across the organization. Key responsibilities include: 1. Design, develop and maintain interactive Power BI dashboards and visual reports for senior stakeholders. 2. Perform deep‑dive data analysis using SQL and advanced modeling techniques to uncover actionable insights. 3. Clean, transform, and integrate data from multiple sources, applying data‑engineering best practices. 4. Implement data quality checks and governance frameworks to guarantee accuracy and consistency. 5. Leverage AI prompting tools to accelerate solution development and automate repetitive analytics tasks. 6. Gather and document business requirements, translating them into technical specifications. 7. Identify process inefficiencies and propose automation or optimization initiatives. 8. Support change management by preparing documentation, training users, and monitoring adoption. 9. Collaborate with data engineers and architects to design scalable data warehouses. 10. Continuously monitor performance of analytics solutions and implement enhancements. Tech stack: SQL, Power BI, Azure Data Factory (or similar ETL tools), Python/R for advanced analytics, AI prompting platforms, data‑warehousing concepts, and standard Microsoft Office suite. Growth path: Starting as an Advanced Data Analyst, high performers can progress to Senior Analyst, Analytics Lead, or Data Product Manager roles, with opportunities to specialize in AI‑driven analytics, data engineering, or business intelligence strategy. Why join CAES by Honeywell? The role offers exposure to industry‑leading projects, mentorship from seasoned professionals, and a platform to innovate with AI and cloud technologies. Employees benefit from a collaborative environment, competitive compensation, and clear career progression, making it an ideal launchpad for fresh talent aspiring to become analytics leaders.