Taguig City, PHL
10 days ago
Senior Data Engineer - Consumer Pulse
Job Location Taguig City Job Description The Opportunity Join us in building the next generation of Consumer Research. Consumer Pulse is at the heart of consumer intelligence. We work with rich data sets (500 million+) such as news media, social media, consumer complaints, product reviews, and many more. We also use modern data engineering techniques and ML / Gen AI to solve large scale problems that have meaningful impact to P&G’s consumers. Our vision is to empower EVERYONE to create and sell superior products by transforming listening signals into FRICTIONLESS & ACTIONABLE intelligence. We do this by capturing & driving clarity of social signals across key OU driven business cases. This enables our users to create value by earning influencer advocacy, growing the reputation of P&G and our brands, and discovering actionable insights. Responsibilities You will be working closely with various Product Managers, Data Scientists, AI Engineers, vendors, and our Data Analysts. Key responsibilities include: + Provide technical leadership and guidance to the Scrum team – can include Data Engineers, analysts, and/or AI Engineers + Transform and optimize our current Data Engineering processes and practices + Design, build, and maintain data pipelines and ETL processes + Implement data integration solutions, including CDL publishing + Optimize for cost & performance + Obsess over data quality + Support, Monitoring & Troubleshooting + Work with the Program Manager to define deliver timelines + Documentation – processes, architectures, standards + Coach other Data Engineers, including vendors Other responsibilities also include: + Solution Architecture and Design + Application Management (incl. internal app. registration) + Tech SPOC for: Enterprise Architects, Info sec, Cloud, Platform, Purchasing, Legal, Data Managers and Data Scientists + Build deep domain expertise + Infrastructure requests and sizing (via. cloud COE) + Information Security + Engineering vendor management Job Qualifications + At least 5 years of experience as a Data Engineer. + Demonstrated leadership skills and team management. If appointed as the tech lead, you may be leading a technical team with members that don’t report to you directly. + Advanced hands-on experience with Databricks PySpark workloads and Azure data services. Our tech stack heavily leans on Databricks, Delta Live Tables, and Azure Data Factory. + Very strong software development foundation including CI/CD, automated testing, and quality management. You can envision what a high performing DevOps team looks like and build towards that. + Strong data structures and data modeling foundation. You can design a small/medium scale solution without relying on a data architect. + Strong oral/written communication and collaboration skills. You will be working with a multi-functional global team. + Demonstrated meticulous attention to detail. You have a relentless focus on accuracy and a strong commitment to high-quality outputs. 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 can 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 R000116887 Job Segmentation Experienced Professionals (Job Segmentation)
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