Principal Engineer Data Analytics

General SummaryWe are looking for a highly skilled and experienced Principal Data Engineer to architect and lead the development of our data infrastructure. The successful candidate will possess deep technical expertise in data engineering and will be responsible for designing, building, and managing large-scale data processing systems, ensuring their scalability, reliability, and performance. This role will work closely with data engineering teams, product leads, and business stakeholders in support of Coca-Cola’s North America Operating Unit.Key Responsibilities• Data Pipeline Development:• Design, develop, and maintain scalable and efficient data pipelines using Azure Data Factory, Azure Synapse, PySpark, and other Azure services that support complex data transformations and large-scale processing.• Implement ETL/ELT processes to ingest, transform, and load data from various sources into Azure data storage solutions (e.g., Azure Blob Storage, Azure Data Lake, Azure SQL Database)• Implement and maintain data management frameworks, ensuring data quality, consistency, and security.• Data Modeling and Warehousing:• Develop and maintain data models, schemas, and data warehouses to support business intelligence and analytics needs.• Optimize data storage and retrieval strategies to enhance performance and scalability. Collaboration and Leadership• Data Integration:• Integrate data from multiple sources, including on-premises databases, cloud services, APIs, and third-party systems.• Ensure data quality, consistency, and reliability across all data sources.• Collaboration and Support:• Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand data requirements and deliver efficient solutions.• Troubleshoot and resolve performance bottlenecks and other technical issues related to data infrastructure.• Mentor and guide junior data engineers, providing technical leadership and fostering a culture of continuous improvement and innovation.• Automation and Optimization:• Automate repetitive tasks and processes to improve efficiency and reduce manual intervention.• Continuously monitor and optimize data pipelines for performance and cost-effectiveness.Qualifications• Bachelor’s degree in Computer Science, Engineering, Information Technology, or 10+ year’s experience in the data engineering field• Minimum of 8+ years of experience in data engineering or a related role, with a proven track record of working on large-scale data projects.• Strong expertise in Python and SQL• Proven experience with Azure and its data warehousing (Synapse, Redshift) and big data technologies (e.g., Spark)• Proven experience in designing and building scalable data pipelines and data warehouses.• Deep understanding of database theory, data modeling, and ETL/ELT processes• Demonstrated ability to work in a fast-paced environment, managing multiple projects and deadlines.• Excellent problem-solving skills, attention to detail, and ability to think critically and analytically.Strong communication skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders.Preferred Qualifications• Azure Data Engineer certifications (e.g., Microsoft Certified: Azure Data Engineer Associate).• Experience with DevOps practices and tools, including CI/CD pipelines, version control, and infrastructure as code (e.g., GitHub Actions, Azure DevOps, Terraform).• Experience developing in the Power Platform, specifically Power BI and Power Apps• Additional experience in programming languages Scala, Java, Node.js• Additional experience in AWS Data Lake technologies, such as AWS Redshift and AWS Glue• Experience in the consumer packaged goods industry• Experience with machine learning and AI-driven data processing techniques.$159,300 - $184,700