Sr Analyst, Application Operations
$101,100–$139,000 year
On-siteCamden, New Jersey, United States
Job Summary
Build, monitor, and optimize ETL/ELT pipelines, workflows, and integrations across enterprise data platforms using Databricks, Snowflake, and Azure Data Factory. Perform hands-on SQL and Python analysis to validate data, troubleshoot root causes, and resolve quality or performance issues within SAP S/4HANA and cloud applications. Develop Power BI and MicroStrategy dashboards, maintain semantic layers, and automate efficiency through Python/SQL scripts. Lead incident investigations, manage data administration tasks, and apply AI/ML concepts to support emerging analytics initiatives. This hands-on role within the Data Analytics and AI Operations team at Campbell's drives digital transformation and ensures trusted data availability for stakeholders across Supply Chain, Finance, and Marketing functions.
Required Qualifications
- 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
Desired Qualifications
- 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
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