Sr Analyst, Application Operations

Since 1869, we've connected people through food they love. We’re proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell’s brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao’s Homemade, Snack Factory, Snyder’s of Hanover, Swanson, and V8.

Benefits

• Benefits begin on day one and include medical, dental, short and long-term disability, AD&D, and life insurance (for individuals, families, and domestic partners).
• Employees are eligible for our matching 401(k) plan and can enroll on the first day of employment with immediate vesting.
• Unlimited sick time along with paid time off and holiday pay.
• If in WHQ – free access to the fitness center.
• Access to on-site day care (operated by Bright Horizons) and company store.
• “Campbell’s Cares” program matches employee donations and/or volunteer activity up to $1,500 annually.
• A variety of Employee Resource Groups (ERGs) to support employees.

About the role

As a Senior Analyst – Application Operations, you will be a hands-on member of the Data Analytics and AI Operations team, responsible for operating, monitoring, troubleshooting, and continuously improving enterprise data and analytics platforms. You will bring strong Data Engineering and Data Analytics experience to ensure reliable data pipelines, high-quality data, actionable insights, and trusted analytics. You will leverage industry-leading technologies including Databricks, Snowflake, Azure Data Factory (ADF), Informatica, Python, SQL, MicroStrategy, and Power BI to deliver scalable, secure, and high-performing data solutions. Your work will help drive digital transformation, enable AI innovation, and ensure trusted data is available to stakeholders across the enterprise. You will also apply working knowledge of AI and Machine Learning to support evolving data, analytics, and AI capabilities.

Responsibilities

• Perform hands-on Data Engineering and Data Analytics across enterprise data platforms and solutions.
• Build, monitor, troubleshoot, and optimize ETL/ELT pipelines, workflows, integrations, and data jobs.
• Perform hands-on SQL and Python data analysis, validation, reconciliation, profiling, and root cause analysis.
• Support the data pipelines across SAP S/4HANA, SAP Datasphere, SAP SLT, ERP, APIs, cloud applications, and other enterprise systems.
• Analyze and resolve data quality, pipeline, performance, and integration issues.
• Develop and support Power BI, MicroStrategy, reports, dashboards, KPIs, metrics, and operational analytics.
• Create and maintain trusted data products, curated datasets, and semantic layers that support enterprise analytics and AI use cases.
• Support and maintain curated datasets, semantic layers, data models, and enterprise reporting.
• Support data administration activities, including access, permissions, user management, job scheduling, environment support, monitoring, and data platform operations.
• Develop Python/SQL automation to improve efficiency and reduce manual effort.
• Monitor data and platform performance and proactively identify operational risks.
• Lead incident investigation, troubleshooting, resolution, and corrective actions.
• Maintain runbooks, SOPs, monitoring standards, and technical documentation.
• Drive data quality, governance, security, lineage, metadata, and compliance practices.
• Identify opportunities for automation, optimization, reliability, and continuous improvement.
• Apply knowledge of AI/ML concepts and data requirements to support emerging analytics and AI initiatives.
• Serve as a hands-on technical resource for data and analytics issues.

Who You Will Work With

• Data Engineering teams supporting enterprise data platforms, pipelines, integrations, and data products.
• Analytics and BI teams supporting Power BI, MicroStrategy, reporting, dashboards, and analytics solutions.
• Platform Engineering and Cloud teams supporting Databricks, Snowflake, Azure, monitoring, and reliability.
• Data Science and AI Engineering teams supporting AI, ML, and advanced analytics initiatives.
• Business Owners and Product Owners to align data solutions with business priorities and outcomes.
• Digital Partners and Digital Product teams supporting digital solutions, data products, and integrations.
• Data Governance, Security, and Compliance teams supporting data quality, standards, lineage, and controls.
• Data Architects and Enterprise Architecture teams supporting data strategy and modernization.
• Business stakeholders across Supply Chain, Finance, Sales, Marketing, and Corporate Functions.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Business Analytics, or a related technical field.
• 5+ years of hands-on experience across both Data Engineering and Data Analytics.
• Strong hands-on SQL skills for data analysis, troubleshooting, validation, reconciliation, and root cause analysis.
• Hands-on experience building, monitoring, troubleshooting, and optimizing ETL/ELT pipelines.
• Strong experience with Databricks and/or Snowflake, or similar enterprise data platforms.
• Experience with ADF, Informatica, ADLS, or similar cloud data technologies.
• Hands-on Python experience for data analysis, automation, and operational solutions.
• Hands-on experience with Power BI, MicroStrategy, or similar analytics and reporting platforms.
• Strong understanding of data modeling, data quality, data governance, data lineage, metadata, and data security.
• Experience with production support, incident management, monitoring, and problem resolution.
• Strong troubleshooting, analytical, and problem-solving skills, with the ability to drive issues through resolution.
• Working knowledge of AI and Machine Learning concepts, including common AI/ML use cases, data requirements, and the ML lifecycle.
• Strong communication and stakeholder-management skills across technical and business teams.
• Ability to work independently, take ownership, prioritize effectively, and deliver hands-on solutions.
• Demonstrated ability to drive automation, reliability, efficiency, and continuous improvement.

Nice to Have

• Experience in MLOps, AI Operations, Generative AI, or Agentic AI to enable Machine Learning, Generative AI, and Agentic AI initiatives through scalable, governed, and high-quality data solutions.
• Knowledge of feature engineering, model monitoring, ML/AI pipelines, or AI platforms.
• Knowledge of SAP S/4HANA, SAP Datasphere, SAP SLT, and SAP data integration.
• Experience in Unity Catalog, data catalogs, lineage, and metadata management.
• Experience in data and platform observability tools.
• Certifications in Databricks, Snowflake, Azure, Informatica, Generative AI, or Agentic AI or related is preferred.

Preferred Technical Skills

• Data Engineering: Databricks, Snowflake, PySpark, Python, SQL, ADF, Informatica, ADLS, ETL/ELT, Data Modeling
• Data Analytics & Operations: Data Analytics, Data Operations, Power BI, MicroStrategy, Reporting, Dashboards, KPIs, Production Support, Monitoring, Incident Management, Root Cause Analysis
• Data Governance & Quality: Data Quality, Data Validation, Data Reconciliation, Data Profiling, Data Governance, Data Lineage, Metadata, Data Security, Data Administration
• Knowledge: Platform Administration, Access & Permissions, User Management, Job Scheduling, Environment Management, Data Monitoring
• Automation: Python/SQL Automation, Git, CI/CD, DevOps
• AI & ML Knowledge: AI/ML Fundamentals, ML Lifecycle, Feature Engineering, Model Monitoring, Generative AI, MLOps

Pay

The target base salary range for this full-time, salaried position is between $101,100-$139,000. Individual base pay depends on work location and additional factors such as experience, job-related skills, and relevant education or training. Total pay may include other forms of compensation. In addition, we offer competitive health, dental, 401k, and wellness benefits beginning on the first day of employment.