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Procter & Gamble
Procter & Gamble

Senior Data Engineer - Consumer Data Platform at Procter & Gamble

RoleData Engineering
LevelSenior
LocationMANILA SIX/NEO OFFICE
WorkOn-site
TypeFull-time
Posted1 day ago
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About the role

Job Location

MANILA SIX/NEO OFFICE

Job Description Overview of the job

Join us as a Senior Data & Backend Engineer Developer and be the driving force behind the growth and success of our data platform. You will work with the architects, engineering and product leaders to develop world class data and backend platforms.

Your team

Reporting to the Engineering Director, you'll be part of a dynamic IT team at P&G. Our team leads multi-billion-dollar projects globally, leveraging cutting-edge technologies in mobile, social, cloud, big-data analytics, IoT, and more.

How success looks like

  • Transform product requirements into high-quality business outcomes.

  • Lead the design, and development of data platform and backend applications.

  • Mentor junior developers and keep yourself up to date with the latest technologies.

Responsibilities of the role

  • API Development:

Design, develop, and maintain robust and scalable backend systems and APIs.

  • Data Ingestion:

Develop and maintain data pipelines to extract data from various sources and load it into Google Cloud environments.

  • Data Transformation:

Implement data transformation processes, including data cleansing, normalization, and aggregation, to ensure data quality and consistency.

  • Data Modeling:

Develop and maintain data models and schemas to support efficient data storage and retrieval in Google Cloud platforms.

  • Data Warehousing:

Build data warehouses or data lakes using Google Cloud services such as Big Query.

  • Data Integration:

Integrate data from multiple sources, both on-premises and cloud-based, using Cloud Composer or other relevant tools.

  • Data Governance:

Implement data governance practices, including data security, privacy, and compliance, to ensure data integrity and regulatory compliance.

  • Performance Optimization:

Optimize data pipelines and queries for improved performance and scalability in Google Cloud environments.

  • Monitoring and Troubleshooting:

Monitor data pipelines, identify and resolve performance issues, and troubleshoot data-related problems in collaboration with other teams.

  • Data Visualization:

Build BI reports to enable faster decision making.

  • Collaboration:

Work with product managers to ensure superior product delivery to drive business value & transformation

  • Documentation: Document data engineering processes, data flows, and system configurations for future reference and knowledge sharing.

Job Qualifications

  • Experience:

Bachelor's or master's degree in computer science, data engineering, or a related field, along with 5+ year work experience in data engineering and cloud platforms. Previous experience in a senior or lead engineering role.

  • Google Cloud Development:

Strong proficiency in Google Cloud services such as Spanner, Cloud Composers, Looker Studio, etc. (Microsoft Azure Cloud knowledge will be a plus)

  • ETL Tools:

Experience with ETL (Extract, Transform, Load) tools and frameworks, such as Spark and Cloud Composer/Airflow for data integration and transformation.

  • Programming:

Proficiency in programming languages such as Py Spark, Python, and SQL for data manipulation, scripting, and automation. Data Modeling: Knowledge of data modeling techniques and experience with data modeling tools.

  • Database Technologies:

Familiarity with relational databases (e.g., Cloud SQL) for data storage and retrieval.

  • Data Warehousing:

Understanding of data warehousing concepts, dimensional modeling, and experience with data warehousing technologies such as Big Query.

  • Data Governance:

Knowledge of data governance principles, data security, privacy regulations (e.g., GDPR, CCPA), and experience implementing data governance practices.

  • Data Visualization:

Experience of working with Looker Studio to build semantic data model & BI reports/dashboards.

  • Cloud Computing:

Familiarity with cloud computing concepts and experience working with cloud platforms, particularly Google Cloud Platform.

  • Problem-Solving:

Strong analytical and problem-solving skills to identify and resolve data-related issues. Proficiency in DevOps Tools and CICD tools (e.g. Terraform, Github) Familiarity with Azure, Databricks and its relevant tech stacks would be an advantage to the role.

About us

We produce globally recognized brands and we grow the best business leaders in the industry. With a portfolio of trusted brands as diverse as ours, it is paramount our leaders are able to lead with courage the vast array of brands, categories and functions. We serve consumers around the world with one of the strongest portfolios of trusted, quality, leadership brands, including Always®, Ariel®, Gillette®, Head & Shoulders®, Herbal Essences®, Oral-B®, Pampers®, Pantene®, Tampax® and more. Our community includes operations in approximately 70 countries worldwide.

Visit http://www.pg.com to know more.

We are an equal opportunity employer and value diversity at our company. We do not discriminate against individuals on the basis of race, color, gender, age, national origin, religion, sexual orientation, gender identity or expression, marital status, citizenship, disability, HIV/AIDS status, or any other legally protected factor.

Job Schedule

Full time

Job Number

R000150567

Job Segmentation

Experienced Professionals

Required skills

Data engineering

Backend development

API design

Data modeling

ETL

Cloud architecture

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About Procter & Gamble

Procter & Gamble

Procter & Gamble is a multinational consumer goods corporation that manufactures and markets a wide range of household and personal care products. The company operates through various segments including fabric and home care, beauty, health care, and baby, feminine and family care.

10,001+

Employees

Cincinnati

Headquarters

$386B

Valuation

Reviews

10 reviews

4.0

10 reviews

Work-life balance

3.8

Compensation

4.2

Culture

4.3

Career

2.8

Management

3.7

75%

Recommend to a friend

Pros

Excellent benefits and health benefits

Supportive and inclusive team environment

Flexible working hours and work-life balance

Cons

High-pressure and stressful work environment

Limited career advancement opportunities

Demanding work hours during peak seasons

Salary Ranges

0 data points

Junior/L3

Junior/L3 · Data Scientist

0 reports

-

total per year

Base

-

Stock

-

Bonus

-

Interview experience

5 interviews

Difficulty

3.0

/ 5

Interview process

1

Application Review

2

Online Assessment

3

HR Screen

4

Hiring Manager Interview

5

Final Round Interview

6

Offer

Common questions

Behavioral/STAR

Technical Knowledge

Past Experience

Case Study

Problem Solving