$101,100 – $139,000
Listed on Pepperidge Farm’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role operates and optimizes enterprise data platforms and analytics infrastructure at Campbell's, handling ETL pipelines, data quality, and reporting systems. It suits experienced data engineers and analysts who want hands-on platform ownership and troubleshooting across modern cloud technologies like Databricks and Snowflake.
Our summary, not Pepperidge Farm’s wording. The full posting is on their site.
Skills this role names
- Azure Data Factory
- CI/CD
- Data Modeling
- Databricks
- Git
- Informatica
- MicroStrategy
- Power BI
- PySpark
- Python
- Snowflake
- SQL
Log in to see which of these are already on your profile.
What they ask for
Required
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Business Analytics, or related technical field
- 5+ years hands-on experience in both Data Engineering and Data Analytics
- Strong SQL skills for data analysis, troubleshooting, and validation
- Hands-on experience building, monitoring, and optimizing ETL/ELT pipelines in Databricks and Snowflake
- Strong experience with Databricks and/or Snowflake or similar enterprise data platforms
- Experience with Azure Data Factory, Informatica, ADLS, or similar cloud data technologies
- Hands-on Python experience for data analysis and automation
- Hands-on experience with Power BI, MicroStrategy, or similar analytics platforms
- Understanding of data modeling, data quality, governance, lineage, and security
- Experience with production support, incident management, and problem resolution
- Troubleshooting and analytical problem-solving skills
- Working knowledge of AI and Machine Learning concepts
- Strong communication and stakeholder management skills
- Ability to work independently and drive continuous improvement
Nice to have
- Experience with MLOps, AI Operations, Generative AI, or Agentic AI
- Knowledge of feature engineering, model monitoring, or ML/AI pipelines
- Knowledge of SAP S/4HANA, SAP Datasphere, and SAP SLT
- Experience with Unity Catalog, data catalogs, and metadata management
- Experience with data and platform observability tools
- Certifications in Databricks, Snowflake, Azure, Informatica, or Generative AI