Senior Data Operations & Analytics Engineer

Campbell Soup Company

Camden, Northern (NJ, KY)

Hybrid

USD 101,000 - 139,000

Full time

3 days ago

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Benefits offered by this job

On-site fitness center

On-site day care

Company store

Employee Resource Groups

ERGs and community volunteering

Job summary

Campbell Soup Company is seeking a Senior Analyst – Application Operations to join the Data Analytics and AI Operations team. You will operate, monitor, troubleshoot, and continuously improve enterprise data and analytics platforms to deliver reliable data pipelines and actionable insights.

The role uses Databricks, Snowflake, Azure Data Factory, Informatica, Python, SQL, Power BI and MicroStrategy to enable digital transformation and trusted data for stakeholders across the enterprise, with

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 SQL skills for data analysis, troubleshooting, validation, reconciliation, and root cause analysis.
Hands‑on experience building and optimizing ETL/ELT pipelines with Databricks and Snowflake.
Experience with Databricks and/or Snowflake, or similar enterprise data platforms.
Experience with ADF, Informatica, ADLS, or similar cloud data technologies.
Hands‑on Python for data analysis, automation, and operational solutions.
Hands‑on experience with Power BI, MicroStrategy, or similar analytics platforms.
Strong understanding of data modeling, data quality, governance, lineage, metadata, and data security.
Experience in production support, incident management and monitoring.

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 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 analytics and AI use cases.
Support data administration activities, including access, permissions, user management, job scheduling, environment support, monitoring, and platform ops.
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.
Apply knowledge of AI/ML concepts to support evolving analytics and AI initiatives.