Role Description & Responsibilities
Data Engineering
About P&G
P&G is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Data Engineering role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
As a Data Engineer - North America Fabric Care at P&G, you will join an innovative team focused on building scalable, data-driven solutions. Design, build, and maintain scalable data pipelines, data lakehouse architectures, and streaming infrastructure that power mission-critical analytics and machine learning systems.
This opening provides direct commercial exposure, structured technical mentorship, and the opportunity to contribute to production workflows across P&G's core business domains.
Key Responsibilities & Day-to-Day Scope
- ✓ Develop robust, fault-tolerant batch and streaming ETL/ELT pipelines using Python, SQL, and Apache Spark / PySpark.
- ✓ Design and maintain dimensional data warehouse schemas and lakehouse tables (Delta Lake, Iceberg, Snowflake, BigQuery).
- ✓ Implement data orchestration and workflow schedules using tools like Apache Airflow, Prefect, or Dagster.
- ✓ Ensure data quality, integrity, and governance by writing automated validation tests and anomaly monitors.
- ✓ Partner with data scientists and analytics teams to optimize query performance and model feature accessibility.
Official Qualifications & Technical Requirements
- • Enrolled in or completed a degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
- • Strong coding proficiency in Python and advanced SQL (including performance optimization and indexing).
- • Working knowledge of data pipeline concepts, distributed storage, and relational database internals.
- • Understanding of software engineering best practices: version control (Git), modular architecture, and CI/CD.
- • A detail-oriented mindset with high standards for data accuracy and system resilience.
Preferred Skills & Technology Stack
- + Experience with big data tools (Apache Spark, Kafka, Flink) and cloud platforms (AWS, Azure, GCP).
- + Familiarity with dbt (data build tool) for SQL transformations.
- + Hands-on experience with Docker and Linux system administration.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at P&G
Verified EmployerP&G champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.