JOB PROFILE: Purpose of the Position As a hands-on Data Management Analyst within the Data Engineering and Science (DES) team, you will drive cloud data strategy, semantic modeling, pipeline automation, and global business intelligence. You will serve as a key technical contributor across core analytics initiatives—translating complex raw data into unified cloud-native semantic layers, automating data transformations for Operations Research (OR) models, and taking full ownership of mission-critical global executive dashboards. Core Responsibilities 1. Cloud Ontology & Semantic Layer Development
• Design, build, and govern scalable Ontology and Semantic layers natively within modern cloud data platforms (Databricks, GCP, and/or Azure).
• Define unified business logic, domain entities, relationships, and standardized metrics across cloud lakehouse architectures to establish a single source of truth for downstream analytics and AI/BI consumption.
• Partner with data architects and engineers to ensure semantic models are optimized for performance, discoverability, and self-service analytics in a 100% cloud-native environment. 2. Data Sourcing, Python Transformation & Pipeline Automation
• Source, extract, and assist in data ingestion from diverse operational, transactional, and enterprise source systems.
• Good experience with clean, modular, and efficient Python code to clean, transform, and shape complex datasets tailored specifically for Operations Research (OR) and advanced analytics consumption.
• Collaborate closely with engineers to design, and help in execution of end-to-end automation strategies for cloud data pipelines and data preparation workflows. 3. Global BI Ownership & Executive Analytics Support
• Assist in end-to-end ownership of global Business Intelligence dashboards and enterprise reporting products, ensuring high availability, data accuracy, and actionable insights.
• Provide hands-on BI and analytical support for flagship operational and executive visibility platforms.




• Partner with global stakeholders and visualization teams to standardize KPIs, enhance user experience, and deliver high-impact analytical solutions that drive strategic decision-making. 4. Hands-on Cloud Analytics & AI / Operations Research (OR) Initiatives
• Serve as an active, hands-on technical data analyst in Artificial Intelligence (AI), Machine Learning, and Operations Research (OR) projects.
• Leverage Cloud platform and query expertise (Advanced SQL, Python, Spark/Databricks, Cloud Lakehouses) to perform root-cause diagnostic analysis, validate model inputs/outputs, and resolve complex data challenges. Requirements &

Qualifications:
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Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Engineering, Analytics, or a related quantitative field.
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Experience:
• Data Management Analyst: 5-8 years of hands-on experience in data analytics, data engineering, or cloud data management.
• Senior Data Management Analyst: 5–8+ years of progressive hands-on experience leading cloud data modeling, pipeline automation, and enterprise BI initiatives.
• Technical Skills (Must-Have):
• Strong hands-on proficiency in Python (Pandas, PySpark, data transformation scripting) and advanced SQL.
• Proven experience working natively in modern cloud ecosystems (Databricks, GCP, and/or Microsoft Azure).
• Good to have expertise in building Cloud Ontology / Semantic layers, unified metric layers, and cloud lakehouse data models.
• Good practical proficiency in enterprise BI and visualization platforms (e.g., Power BI, Tableau, or equivalent up-to-date BI tools) with experience owning production-grade global dashboards.
• Key Assets (Good-to-Have):
• Direct, hands-on participation in Operations Research (OR), optimization modeling, or AI/ML project lifecycles.
• Experience with RESTful API integrations, workflow orchestration, and pipeline automation tools.
• Relevant Cloud (Databricks, Azure, GCP) or Agile/SAFe certifications.

📌 DATA MANAGEMENT ANALYST (Bengaluru)
🏢 FedEx
📍 Bengaluru