Job Description

Job Overview: Why join us? Keurig Dr Pepper (NASDAQ: KDP) is a modern, leading coffee and beverage company with a bold vision built to deliver growth and opportunity. We operate with a differentiated business model and world-class brand portfolio, powered by a talented and engaged team that is anchored in our values. We seek diversity in our workforce and empower our team of ~28,000 employees to develop and grow. We care for our employees’ health, wellness, personal and financial well-being by offering robust benefits. We work with big, exciting beverage brands and the #1 single-serve coffee brewing system in North America at KDP, and we have fun doing it! Come be a part of a company where you can feel valued, inspired, and appreciated at work. What we are looking for: Keurig Dr Pepper is seeking a Senior Principal Data Engineer, Data Analytics who can collect, store, and enable the analysis of data at scale. As a Senior Principal Data Engineer, Data Analytics you will… Build & manage the data integrations necessary to support value creation, growth, and delivery of business and IT results. Design and implement the data and analysis infrastructure, including complex databases. Develop different technical tools/services to enable large scale machine learning solutions. Work closely with Architects, Data Analysts, and others to determine what data management systems are appropriate and which data is needed for analysis. Work closely with Data Analysts and Data Scientists, and others to develop scalable and production ready Advanced Analytics and supporting software. Build and maintain data management systems that combine core data sources into data warehouses or other accessible structures to support reporting and analytical systems. Who you are: Deep Knowledge of system development life cycle (SDLC) methodologies (e.g., waterfall, spiral, SAFe, agile, rapid prototyping, incremental, synchronize and stabilize and DevOps). Deep knowledge in the following areas: Languages such as (R, Python, Scala etc.). Commercial data science platforms (e.g., Python, R, KNIME, Alteryx, etc.). Modern data storage and access technologies, including caching, application of NoSQL, Key/Value, and RDBMS datastores. SQL, PL/SQL, SnowSQL and Oracle. Extract-Transform-Load (ETL) processing and Change Data Capture (CDC) technologies. Business intelligence tools (such as Tableau, Qlik, PowerBI). Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management. Directory Services (E.g., Windows 2000+ AD, LDAP) and Internet Protocols (E.g., DNS, SMTP, SSL). Lead a team, setting strategy, and monitoring progress towards goals. Strong communication skills, facilitate business requirements gathering. Proven ability to build, manage and optimize data pipelines that facilitate data movement. Proven ability to reduce manual data work and improve productivity. Proven ability to build robust data operations and to identify critical issues faster in order to debug and troubleshoot quickly. Proven ability to articulate and solve problems or answer questions with data. Proven ability to turn data insights into recommendations for both clients and internal stakeholders based on context. Proven ability to communicate technical information to other technical team members but also to coworkers in other departments who may not have knowledge of technical terminology. Total Rewards: Benefits, subject to election and eligibility: Medical, Dental, Vision, Disability, Paid Time Off (including paid parental leave, vacation, and sick time), 401k with company match, Tuition Reimbursement, and Mileage Reimbursement. Annual bonus based on performance and eligibility. Requirements: Bachelor’s or Master’s degree in related field (e.g., Computer Science, Data Science, Software Engineering, Information Systems, etc.) or equivalent combination of education and work experience. Typically, 5+ years of experience in data management disciplines, including data integration, modeling, optimization, and data quality, or other areas directly relevant to data engineering responsibilities and tasks. 5+ years of gathering and analyzing data, creating visualizations. Native-level proficiency/fluent in English. Experience in DevOps and Agile technology environments. (preferred) #J-18808-Ljbffr Keurig Dr Pepper

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