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In office (Bengaluru)
Seniority
Senior · 5+ years exp
Visa
Sponsors visas in United States; no register of this country names it

First seen by Alion on Nov 13, 2026.

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FedEx is a global transportation and logistics company headquartered in Memphis, Tennessee, providing express parcel delivery, ground and freight shipping, customs brokerage and e-commerce logistics services. Founded as Federal Express in 1971, it operates one of the largest cargo air fleets in the world and serves more than 220 countries and territories; the job board of this record covers the FedEx Express Latin America and Caribbean region. It hires couriers, customs agents and specialists, operations and logistics agents, maintenance technicians, payroll and legal staff and account executives in Mexico, Brazil, Colombia and other countries in the region.
Backed by Matrix, Amethis

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 :

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.

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.

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.

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 :

- Education : Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, Engineering, Analytics, or a related quantitative field.

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 modern 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.

Skills

Data Analyst, Data Analytics, Data Management, Power BI, Pandas, Ontology Engineering, PySpark, Cloud, Tableau

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