# Data Engineering Senior Manager - Consumer Data Platform at Procter & Gamble

Procter & Gamble is hiring a Data Engineering Senior Manager - Consumer Data Platform. Level rates it Little AI ●○○○; you can [apply on Procter & Gamble](https://jobsbylevel.com/go/4a65177d-ce1b-41ae-905a-2971c533038a?utm_medium=ai-agent).

AI Level 1, AI centrality 0 out of 100. MANILA NET PARK OFFICE.

## Details

- Company: [Procter & Gamble](https://jobsbylevel.com/companies/procter-gamble)
- AI level: AI Level 1 (score 0 out of 100)
- Location: MANILA NET PARK OFFICE
- Posted: August 24, 2026
- Apply: https://jobsbylevel.com/go/4a65177d-ce1b-41ae-905a-2971c533038a?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=data-engineering-senior-manager-consumer-data-platform-at-procter-gamble-ebffe5

## Prepare for this job

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## Description

Job Location MANILA NET PARK OFFICE Job Description At P&G, your career is built to scale with our iconic brands like Ariel ® , Safeguard ® , Tide ® , Head & Shoulders ® , Old Spice ® , and Vicks ®. Ready to join the team that powers our iconic brands? Here’s what you’ll be doing: Overview of the job Join us as a Senior Data Engineer responsible for working with global first party Consumer Data Platform. You will work with engineering, operations and product leaders to ensure that our Consumer Data Platform opens new business opportunities while securing and governing our consumer’s personal data. Your team Reporting to the Engineering Director, you’ll be part of a global, dynamic IT team at P&G. Our team is responsible for working across all P&G brands across the world and managing their first party engagement leveraging cutting edge-technologies across event-driven architecture, integrations across multiple systems and big-data analytics. What success looks like Transform product requirements into high-quality software features. Lead the design and development of the data platform in Google Cloud Platform. Mentor junior developers and keep yourself up to date with the latest technologies. Responsibilities of the role 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, streaming schema validation and aggregation, to ensure data quality, completeness and consistency. Data Modeling: Develop and maintain data models and schemas to support efficient data storage and retrieval in Google Cloud platforms using multiple database technologies – CloudSQL, BigQuery and Cloud Spanner. Data Warehousing: Build data warehouses or data lakes using Google Cloud services such as Big Query. Data Integration: Integrate data from multiple sources using integration tools like Managed Airflow, Dataflow, Dataform 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 database performance, balancing both scale and cost to ensure efficient data operations. Monitoring and Troubleshooting: Monitor database performance using the latest observability tools and troubleshoot data-related problems in collaboration with other teams. Data Visualization: Build data structures to support responsive front ends and build our data dashboards and 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 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, BigQuery, Cloud Composers or equivalent experience in other cloud-environments ETL Tools: Experience with ETL (Extract, Transform, Load) tools and frameworks, such as Spark, Dataflow and Cloud Composer/Airflow for data integration and transformation. Programming: Proficiency in programming languages such as Python, Java and SQL for data manipulation, scripting, and automation. Data Modeling : Knowledge of data modeling techniques and experience with data modeling tools. Relational Database Technologies: Familiarity with relational databases (e.g., Cloud SQL, Cloud Spanner) for efficient data storage and retrieval. Data Warehousing: Understanding of data warehousing concepts, dimensional modeling, and experience with data warehousing

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