FEDEX Hiring Senior Data Engineer in Singapore🇸🇬 Salary S$ 6000/month Apply Online

Company:	FEDEX
Job Role:	Senior Data Engineer - Air Network Planning.
Experience:	(2-3 years).
Vacancy:	10+
Qualification:	Bachelor’s degree in Computer Science or equivalent.
Salary:	S$ 6000/month
Location:	Singapore.
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Apply Mode:	(Online)
Deadline:	Not Mentioned

About the Company:

Description

Business Intelligence & Analytics Systems and Solutions; Implement Business Intelligence & Analytics systems and solutions; full stack and functional design of data warehouse; self-service data exploration; reporting and analysis applications; data modeling; data security and federation strategies; Business Intelligence production processes and best practices; user training and support; vendor management; project management; business case development

Purpose of Position

This role is responsible for designing, building, and maintaining scalable, reliable, and high‑quality data pipelines to support Air Network Planning analytics, digital products, and decision‑support use cases. You will focus on end‑to‑end ETL/ELT development, data integration, and data platform enablement—ensuring that analytical and operational teams have timely, trusted, and well‑modelled data. The role works closely with Data Analysts, Data Scientists, and business stakeholders to translate planning and engineering needs into enterprise‑grade data solutions.

Areas of Responsibility

1 – Data Engineering & ETL Development

• Design, build, and maintain robust ETL/ELT pipelines ingesting data from multiple internal and external sources
• Develop batch and, where applicable, streaming data pipelines using Azure and Databricks
• Implement data transformations, validations, and enrichment logic to produce analytics‑ready datasets
• Ensure data quality, lineage, observability, and reliability of production pipelines
• Optimize pipeline performance, scalability, and cost efficiency

2 – Data Platform & Architecture Support

• Contribute to the design and evolution of the Air Network data platform on Azure
• Work with Databricks (Spark, Delta Lake) to implement scalable data processing and storage patterns
• Collaborate with enterprise platform and security teams to ensure compliance with data governance, access control, and security standards
• Support migration of manual or semi‑automated processes into fully automated, production‑grade pipelines

3 – Analytics & Business Enablement

• Partner with Data Analysts and Data Scientists to enable downstream analytics, dashboards, and advanced models
• Translate business and planning requirements into well‑structured data models and pipelines
• Support strategic Air Network initiatives by delivering reliable datasets for planning, performance evaluation, and optimization use cases
• Document data pipelines, schemas, and integration logic so solutions are reusable and maintainable

To Be Successful in This Role, You Will Need

• Bachelor’s degree or equivalent in Computer Science, Data Engineering, Engineering, Information Systems, or a related discipline
• 4+ years of hands‑on data engineering experience
• Strong experience building production ETL pipelines and data workflows

Technical Skills (Required / Strongly Preferred)

• Azure data ecosystem (e.g., Azure Data Factory, Azure Data Lake, Azure Synapse or equivalent)
• Databricks / Apache Spark, including Delta Lake concepts
• Strong SQL skills and experience with data modeling (star/snowflake, analytics‑optimized schemas)
• Programming experience in Python (or equivalent) for data engineering workflows
• Experience with orchestration, scheduling, and monitoring of data pipelines
• Understanding of data quality checks, error handling, logging, and alerting

Technical Skills (Nice to Have)

• Experience supporting BI tools (e.g., Power BI) through well‑designed data layers
• Familiarity with CI/CD, version control, and DevOps practices for data pipelines
• Exposure to operations research, optimization, or forecasting data use cases
• Experience working in Agile / SAFe environments

Professional Skills

• Strong problem‑solving mindset and attention to data quality
• Ability to work across technical and business teams
• Clear communication and documentation skills
• Good planning, prioritization, and stakeholder management skills

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