Overview Seeking a Manager, Data Operations, to support our growing data organization. In this role, you will play a key role in maintaining data pipelines and corresponding platforms (on-prem and cloud) while collaborating with global teams on DataOps initiatives. Manage the day-to-day operations of data pipelines, ensuring governance, reliability, and performance optimization on Microsoft Azure. This role requires hands-on experience with Azure Data Factory (ADF), Azure Synapse Analytics, Azure Databricks, real-time streaming architectures, and DataOps methodologies. Ensure availability, scalability, automation, and governance of enterprise data pipelines supporting analytics, AI/ML, and business intelligence. Support DataOps programs, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. Assist in implementing real-time data observability, monitoring, and automation frameworks to improve data reliability, quality, and operational efficiency. Contribute to the development of governance models and execution roadmaps to optimize efficiency across data platforms, including Azure, AWS, GCP, and on-prem environments. Work on CI/CD integration, data pipeline automation, and self-healing capabilities to enhance enterprise-wide data operations. Collaborate on building and supporting next-generation Data & Analytics platforms while fostering an agile and high-performing DataOps team. Support the adoption of Data & Analytics technology transformations, ensuring full sustainment capabilities and automation for proactive issue identification and resolution. Partner with cross-functional teams to drive process improvements, best practices, and operational excellence within DataOps. Responsibilities Support the implementation and optimization of enterprise-scale data pipelines using Azure Data Factory (ADF), Azure Synapse Analytics, Azure Databricks, and Azure Stream Analytics. Assist in managing end-to-end data ingestion, transformation, orchestration, and storage workflows, ensuring data reliability, integrity, and availability. Ensure seamless batch, real-time, and streaming data processing while focusing on high availability and fault tolerance. Contribute to DataOps automation initiatives, including CI/CD for data pipelines, automated testing, and version control using Azure DevOps, Terraform, and Infrastructure-as-Code (IaC). Collaborate with Data Engineering, Analytics, AI/ML, CloudOps, and Business Intelligence teams to enable data-driven decision-making. Work with IT, data stewards, and compliance teams to align DataOps practices with regulatory and security requirements. Support data operations and sustainment efforts, including testing and monitoring processes to support global products and projects. Assist in data capture, storage, integration, governance, and analytics initiatives, collaborating with cross-functional teams. Manage day-to-day DataOps activities, ensuring adherence to service-level agreements (SLAs) and business requirements. Engage with SMEs and business stakeholders to align data platform capabilities with business needs. Participate in the Agile work intake and management process to support execution excellence for data platform teams. Collaborate with cross-functional teams to troubleshoot and resolve issues related to cloud infrastructure and data services. Assist in developing and automating operational policies and procedures to improve efficiency and service resilience. Support incident response and root cause analysis, contributing to self-healing mechanisms and mitigation strategies. Foster a customer-centric environment, advocating for operational excellence and continuous service improvements. Contribute to building a collaborative, high-performing team culture focused on automation and efficiency in DataOps. Adapt to shifting priorities and support cross-functional teams in maintaining productivity while meeting business goals. Leverage technical expertise in cloud and data operations to improve service reliability and scalability. Qualifications 12+ years of technology work experience in a large-scale global organization, with CPG industry experience preferred. 12+ years of experience in Data & Analytics roles, with hands-on expertise in data operations and governance. 8+ years of experience working within a cross-functional IT organization, collaborating with multiple teams. 5+ years of experience in a management or lead role, with a focus on DataOps execution and delivery. Hands-on experience with Azure Data Factory (ADF) for orchestrating data pipelines and ETL workflows. Proficiency in Azure Synapse Analytics, Azure Data Lake Storage (ADLS), and Azure SQL Database. Familiarity with Azure Databricks for large-scale data processing (basic troubleshooting or support scope is sufficient if not engineering-focused). Exposure to cloud environments (AWS, Azure, GCP) and understanding of CI/CD pipelines for data operations. Knowledge of structured and semi-structured data storage formats (e.g., Parquet, JSON, Delta). Excellent communication skills, with the ability to empathize with stakeholders and articulate technical concepts to non-technical audiences. Strong problem-solving abilities, prioritizing customer needs and advocating for operational improvements. Customer-focused mindset, ensuring high-quality service delivery and operational excellence. Growth mindset, with a willingness to learn and adapt to new technologies and methodologies in a fast-paced environment. Experience in supporting mission-critical solutions in a Microsoft Azure environment, including data pipeline automation. Familiarity with Site Reliability Engineering (SRE) practices, such as automated issue remediation and scalability improvements. Experience driving operational excellence in complex, high-availability data environments. Ability to collaborate across teams, fostering strong relationships with business and IT stakeholders. Experience in data management concepts, including master data management, data governance, and analytics. Knowledge of data acquisition, data catalogs, data standards, and data management tools. Strong analytical and strategic thinking skills, with the ability to execute plans effectively and drive results. Proven ability to work in a fast-changing, complex environment, adapting to shifting priorities while maintaining productivity.