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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Analyst, Application Operations - **Company:** Campbell Soup Company - **Location:** Camden, NJ, United States - **Experience:** Expert - **Salary:** $101,100.0 - $139,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Information Systems, Continuous Integration, Data Validation, Data Control, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Profiling, Data Security, Data Systems, DevOps, Monitoring of Systems, Job Scheduling, Python (Programming Language), Machine Learning, Metadata, Meta-Data Management, Metadata Repositories, MicroStrategy, Power BI, Standard Sql, DataOps, SAP (Applications), SAP NetWeaver Data Management, SQL Databases, Systems Integration, Enterprise Data Management, Enterprise Software Applications, Feature Engineering, Azure Data Factory, Informatica Powercenter, Snowflake, Grafana, Software Troubleshooting, Generative AI, Data Strategy, Git, Data Layers, AI Platforms, Pyspark, Information Technology, Data Lineage, Data Analytics, SAP S/4HANA, Data Management, Machine Learning Operations, Tools for Reporting, Virtual Agents, Data Pipelines, User Administration, Databricks - **Published:** August 20, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18008581?backUrl=%2Fcareer%2F18008581%2FSr-Analyst-Application-Operations-New-Jersey-Camden ## About the Role * 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 Databricks and Snowflake * 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. IT WOULD BE GREAT IF YOU HAVE... (NICE TO HAVE) * Experience inMLOps, 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 offeature engineering, model monitoring, ML/AI pipelines, or AI platforms. * Knowledge ofSAPS/4HANA, SAP Datasphere, SAP SLT, and SAP data integration. * Experience inUnity Catalog, data catalogs, lineage, and metadata management. * Experience indata and platform observability tools. * Certificationsin Databricks, Snowflake, Azure, Informatica, Generative AI, or Agentic AIor 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 ## Description As aSenior Analyst - Application Operations, you will be a hands-on member of theData Analytics and AI Operations team, responsible for operating, monitoring, troubleshooting, and continuously improving enterprise data and analytics platforms. You will bring strongData Engineering and Data Analytics experienceto ensure reliable data pipelines, high-quality data, actionable insights, and trusted analytics. You will leverage industry-leading technologies includingDatabricks, Snowflake, Azure Data Factory (ADF), Informatica, Python, SQL, MicroStrategy and Power BIto 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 ofAI and Machine Learningto support evolving data, analytics, and AI capabilities. The technologies and responsibilities listed below arenot limited tothose specifically identified. WHAT YOU WILL DO... * 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 teamssupporting enterprise data platforms, pipelines, integrations, and data products. * Analytics and BI teamssupporting Power BI, MicroStrategy, reporting, dashboards, and analytics solutions. * Platform Engineering and Cloud teamssupporting Databricks, Snowflake, Azure, monitoring, and reliability. * Data Science and AI Engineering teamssupporting AI, ML, and advanced analytics initiatives. * Business Owners and Product Ownersto align data solutions with business priorities and outcomes. * Digital Partners and Digital Product teamssupporting digital solutions, data products, and integrations. * Data Governance, Security, and Compliance teamssupporting data quality, standards, lineage, and controls. * Data Architects and Enterprise Architecture teamssupporting data strategy and modernization. * Business stakeholdersacross Supply Chain, Finance, Sales, Marketing, and Corporate Functions. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [#90DaysOfDevOps - The DevOps Learning Journey](https://www.wearedevelopers.com/videos/548-90daysofdevops-the-devops-learning-journey) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Best Coding Boot Camps in Germany](https://www.wearedevelopers.com/magazine/237-best-coding-boot-camps-in-germany)