Senior Manager, Data Engineering

Employment Type: Full-Time A Fortune 500 Consumer Goods organization is seeking a Senior Manager, Data Engineering to lead the strategy, architecture, and delivery of a next-generation cloud data platform centered around Databricks and modern cloud technologies. This is a high-impact leadership opportunity to play a critical role in a large-scale enterprise data transformation program, driving the adoption of scalable data architecture, cloud modernization, advanced analytics, and AI capabilities across the organization. The successful candidate will lead a team of data engineers and platform specialists responsible for building and scaling a cloud-native data ecosystem that supports operational reporting, business intelligence, machine learning, and enterprise-wide data products. This role combines technical leadership, people management, platform strategy, and stakeholder engagement, with a strong focus on Databricks, cloud architecture, governance, and engineering excellence. We are specifically seeking a leader with a proven track record of building and scaling enterprise data engineering teams while delivering large-scale Databricks and cloud platform initiatives. Candidates with deep experience in data modernization, cloud transformation, and Databricks-centered architectures are strongly encouraged to apply. Key Responsibilities Lead and manage a team of Data Engineers, Platform Engineers, and Technical Leads responsible for delivering enterprise data solutions Define and execute the organization's cloud data engineering strategy, standards, and roadmap Drive the architecture, implementation, and optimization of a modern data platform built on Databricks and cloud technologies Establish scalable Lakehouse architectures leveraging Databricks, Delta Lake, Apache Spark, and cloud-native services Partner with business stakeholders, analytics teams, architects, and technology leadership to deliver data capabilities aligned to strategic objectives Own data engineering best practices, including coding standards, data quality frameworks, monitoring, observability, and operational excellence Lead the design and implementation of data governance, security, privacy, and compliance controls across the platform Oversee the development and modernization of data pipelines supporting analytics, reporting, AI, and operational workloads Drive cloud adoption initiatives across Azure, AWS, or Google Cloud environments Establish CI/CD practices, Infrastructure-as-Code standards, and platform automation strategies Manage platform scalability, performance optimization, reliability, and cost management initiatives Collaborate with architecture and security teams to ensure enterprise standards are met Mentor engineering leaders and team members, fostering a culture of innovation, accountability, and continuous improvement Influence executive stakeholders and contribute to long-term enterprise data and AI strategy Required Qualifications 10+ years of experience in Data Engineering, Data Architecture, or Cloud Data Platform roles 5+ years of experience leading Data Engineering teams in enterprise environments 3+ years of hands-on experience with Databricks Proven experience delivering large-scale cloud data platform implementations and modernization initiatives Strong expertise with Databricks, Delta Lake, Apache Spark, and PySpark Experience designing and implementing modern Lakehouse architectures Deep understanding of enterprise data management, governance, security, and data quality frameworks Strong experience with Azure, AWS, or Google Cloud Platform Advanced proficiency in Python and SQL Experience implementing CI/CD pipelines, DevOps practices, and Infrastructure-as-Code solutions Strong knowledge of distributed data processing, cloud architecture, and data platform scalability Demonstrated success managing technical teams, developing engineering talent, and leading complex programs Excellent communication, stakeholder management, and executive presentation skills Preferred Qualifications Experience leading enterprise Databricks transformation initiatives Expertise with Unity Catalog, Delta Live Tables, Databricks Workflows, MLflow, and Databricks Asset Bundles Experience supporting advanced analytics, machine learning, and AI initiatives Experience within consumer goods, retail, CPG, manufacturing, or other large-scale operational environments Cloud certifications in Azure, AWS, or Google Cloud Platform Experience managing globally distributed engineering teams What We’re Looking For We are looking for an experienced Data Engineering leader who combines strong technical depth with proven leadership capabilities. The ideal candidate has successfully built and scaled high-performing data engineering organizations while leading enterprise cloud and Databricks transformation initiatives. This individual will be a strategic partner to technology and business leadership, capable of driving platform modernization, establishing engineering excellence, and enabling the organization’s long-term analytics and AI ambitions through a world-class cloud data platform. #J-18808-Ljbffr