APAC Data and Analytics Specialist – Digital Intelligence

United Parcel Service, Inc.; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

UPS에서 APAC 지역의 데이터 및 분석 전문가로서 Digital Intelligence 팀을 돕고, 고객의 단일 뷰(Single View of Customer) 구축을 위한 데이터 모델링과 분석 솔루션을 개발합니다.

데이터 파이프라인 구성, 데이터 품질 관리, 재사용 가능한 Power BI 모델과 리포트를 설계하여 마케팅 및 고객 분석에 활용합니다. Python으로 자동화 및 데이터 조작을 수행하며 협업 능력과 문제 해결 능력이 중요합니다.

Qualifications

• 데이터 분석/BI 관련 학사 또는 동등한 학위 소지자 필수.
• Power BI/Power Query 동작에 대한 실무 경험 필수 또는 포트폴리오 제시 가능자 우대.
• SQL 역량과 관계형 데이터베이스/데이터 웨어하우스 경험 필수.
• Python 사용 경험 및 데이터 파이프라인 구현 경험 우대.

Responsibilities

• APAC Single View of Customer를 지원하는 데이터 모델 및 분석 솔루션 개발.
• 데이터 통합, 변환, 데이터 파이프라인 설계 및 자동화 구현.
• Power BI 모델링 및 재사용 가능한 리포트 구성, 문서화 유지.

Skills

Power BI

Power Query

SQL

Python

데이터 모델링

ETL/데이터 준비

Education

데이터 분석/데이터 사이언스 관련 학사

Tools

Power BI

Power Query

SQL

Python

데이터 웨어하우스

Job description

직무 지원 이전에 이 페이지의 오른쪽 상단에 있는 옵션에서 언어 환경설정을 선택합니다.

Fortune Global 500에 선정된 기업에서 다음과 같은 기회를 경험할 수 있습니다. 가능성을 혁신 및 구상하고, 보상 문화를 경험하며, 매일 더 나아질 수 있도록 지원하는 인재 팀과 협력할 수 있습니다. UPS를 더 발전된 내일로 이끄는 것은 바로 역량과 열정을 지닌 사람입니다. 역량을 보유하고, 자기 자신은 물론 팀을 이끌 수 있는 인재를 위해 기술을 배양하고 다음 단계로 나아갈 수 있게 할 직무들이 준비되어 있습니다.

직무 설명:

The APAC Data and Analytics Specialist – Digital Intelligence supports the regional Digital Intelligence team in building scalable customer, campaign, and marketing analytics capabilities across Asia Pacific. This role is responsible for developing the technical foundation for Single View of Customer, integrating and transforming data from enterprise and marketing platforms, automating recurring analytical processes, and enabling reusable Power BI reporting and data models. The role uses efficient and advanced analytics to derive insights and to support customer engagement, commercial growth, and informed decision-making.

Job Responsibilities

Customer Intelligence and Single View of Customer

• Translate customer and marketing business requirements into scalable data models, datasets, and analytical solutions supporting the APAC Single View of Customer.
• Integrate available customer/account information, shipment and revenue performance, product or service usage, customer segmentation, and marketing engagement data into reusable customer-level analytical structures.
• Support the development of relationships between UPS ID holders and account holders where data and identifiers allow, and enable analysis across relevant customer populations and sales coverage segments.
• Develop approaches to retain and analyze customer history over time, including changes that may no longer be visible in current monthly source files.
• Partner with Customer and Campaign Intelligence stakeholders to implement agreed customer lifecycle, campaign, and KPI definitions in analytical models and reporting solutions.

Data Integration, Automation, and Power BI

• Extract, combine, transform, and validate data from enterprise data warehouses, CRM/marketing platforms, and other approved data sources using Power Query, SQL, and other appropriate tools.
• Develop repeatable ETL and data preparation workflows that reduce manual effort, improve consistency, and support recurring customer, campaign, and performance analytics.
• Design and maintain reusable Power BI semantic models, DAX measures, and reporting solutions rather than isolated one-off dashboards.
• Improve data quality, refresh reliability, model performance, and documentation, including source-to-report logic, transformations, dependencies, and validation checks.
• Support the prioritized migration of Microsoft Access and spreadsheet-based analytical processes toward more scalable and maintainable solutions.
• Use Python where data scale, complexity, automation, or analytical requirements make it appropriate.

Analytics Enablement and Team Capability

• Enable standardized campaign analytics, customer segmentation, lifecycle analysis, reactivation, cross-sell, and customer growth analysis through reliable datasets and analytical tools.
• Support customer-level analytics for strategic programs, including preparation of analytical views and measurement datasets.
• Progressively support advanced analytical use cases such as clustering, propensity analysis, at-risk identification, experimentation, and recommendation analytics as the data foundation matures.
• Provide technical guidance and reusable components that enable other Digital Intelligence team members to develop and maintain their own Power BI reporting and analysis.
• Partner with regional, country, Corporate, IT, and external vendor stakeholders as required to support scalable analytics solutions and productionization.

Job Requirements

• Possess a Bachelor’s Degree in Business Analytics, Data Analytics, Marketing, Data Science, Information Systems, Computer Science, Statistics, Engineering, or a related discipline.
• 2–5 years of relevant experience in data analytics, business intelligence, data engineering, marketing analytics, or a related function. Candidates with strong hands‑on project experience may also be considered.
• Strong hands‑on experience with Power BI and Power Query, including data modeling and dashboard/report development. Portfolio or dashboard samples are highly encouraged.
• Strong SQL skills and experience working with relational databases, enterprise data warehouses, or large transactional datasets.
• Sound understanding of data modeling, ETL/data preparation, data validation, and combining multiple data sources at different levels of detail.
• Strong analytical and structured problem-solving skills, with the ability to translate business questions into practical data and BI solutions.
• Effective communication skills, with the ability to present technical insights to business stakeholders.
• Experience with Python for data manipulation, automation, or analytics is strongly preferred. Familiarity with DAX, CRM/marketing data, Oracle, historical/snapshot data, or campaign measurement is an advantage.
• Attention to detail and ability to manage multiple priorities in a fast-paced, matrixed, regional environment.
• Collaborative, proactive, adaptable, and willing to learn, with a strong sense of ownership and accountability.

직원 유형:

정규직

UPS는 차별, 괴롭힘 및 보복이 없는 일터를 제공하기 위해 최선을 다하고 있습니다.