Data Analyst

Oracle’s interview process typically starts with an online aptitude test that assesses logical reasoning and basic data interpretation. This is followed by a technical interview where candidates discuss data enrichment techniques, Excel functions, and problem‑solving approaches. The final HR round evaluates communication skills, cultural fit, and career goals. Preparation should focus on real‑world data scenarios and clear articulation of processes.

Oracle is known for its inclusive work culture that encourages innovation and continuous learning. Employees enjoy a balanced work‑life schedule, mentorship programs, and ample opportunities for skill development across cloud and data domains.

Any graduate (Bachelor’s Degree) from any stream; minimum 60% aggregate; no active backlogs; batch year 2023‑2025 preferred; strong communication skills and willingness to learn.

Round 1: Online aptitude & data reasoning test → Round 2: Technical interview focusing on data handling and problem‑solving → Round 3: HR interview covering fit, communication, and career aspirations

Oracle is a global leader in cloud‑based software and hardware solutions, serving enterprises across multiple industries. In India, Oracle operates large development and support centers in cities like Mumbai, Hyderabad, and Bangalore, offering a vibrant ecosystem that blends cutting‑edge technology with a strong focus on customer success. The company’s culture emphasizes continuous learning, diversity, and a collaborative environment where fresh talent can quickly grow into impactful roles. As part of Oracle’s data‑centric product suite, the Analyst team works closely with product managers, data engineers, and client stakeholders to ensure that product information is accurate, enriched, and ready for consumption across e‑commerce and enterprise platforms. The Apprentice Analyst role is designed for recent graduates who are eager to dive into data quality and enrichment projects. The analyst will act as a bridge between raw product data and the polished information that powers client catalogs, search engines, and recommendation engines. By applying standardization, normalization, and categorization techniques, the analyst helps improve data discoverability and ultimately drives better customer experiences for Oracle’s clients. Key responsibilities include: 1. Enriching and filling gaps in online and offline product data by researching multiple sources such as websites, databases, and the internet. 2. Performing data standardization, normalization, and categorization to maintain consistency across product catalogs. 3. Conducting data quality checks and correcting anomalies to meet predefined quality thresholds. 4. Generating basic data profiling reports and presenting insights to stakeholders. 5. Communicating with clients via email for request acknowledgment, project status updates, and query resolution. 6. Assisting customers in enhancing product data from technical specification and description perspectives. 7. Providing technical consulting to category managers on industry best practices for product data enhancement. 8. Collaborating with cross‑functional teams to meet project timelines while upholding high‑quality standards. 9. Documenting processes and creating SOPs for repeatable data enrichment workflows. 10. Continuously learning new tools and techniques to improve data handling efficiency. Technical stack primarily involves MS Office (Excel, PowerPoint), internet research tools, and basic data manipulation utilities. Familiarity with data profiling tools, SQL basics, or scripting languages is a plus. The growth path can lead from Apprentice Analyst to Senior Analyst, then to Data Quality Lead, and eventually to Product Data Manager or Business Analyst roles, with opportunities to transition into broader data analytics or product management tracks. Why join Oracle? The company offers a structured onboarding program, mentorship from seasoned professionals, and exposure to global best practices in data management. Freshers gain hands‑on experience with real‑world data challenges, a competitive salary, and a clear career ladder in a technology‑driven environment.