- Design, build, and operation of batch and streaming data pipelines.
- Ingestion and processing of structured and semi-structured data from sources such as databases, APIs, event streams, logs, and files.
- Data quality, reliability, and observability across data pipelines and platforms.
- Development of clean, maintainable SQL and Python code for data transformations.
- Delivery of high-quality, well-modeled datasets that support analytics and data science teams.
- Application of best practices in data modeling, testing, version control, and documentation.
- Leading and participating in code reviews and technical design discussions to ensure scalable and reliable solutions.
- Staying current with modern data technologies and AI-enabled data workflows and applying them where they add value.
- Multi-facility, high-availability Warehouse management and logistics systems
- Migration toward cloud-native, event-driven architectures
- Azure cloud-native services
- ADF, Python and Azure functions to build data movement pipelines
- Snowflake for real-time data warehousing
- CI/CD-driven delivery model
- Power BI for data visualization
- Application of low-code platforms for process automations
- AI mindset with application of data science models for warehouse optimization, routing, consolidation, and capacity planning
- Professional experience building and supporting data solutions in production environments
- Strong fundamentals in SQL (joins, aggregations, window functions) and Python or a similar programming language
- Solid understanding of core data engineering concepts, including data pipelines and ETL/ELT patterns using tools such as ADF or Informatica
- Experience with data modeling concepts, such as fact and dimension tables
- Understanding of batch and streaming data processing paradigms
- Familiarity with cloud data ecosystems (AWS, Azure, or GCP), with hands‑on or practical experience
- Strong problem‑solving skills, curiosity, and a continuous‑learning mindset
- Hands‑on experience (academic or professional) with:
- Understanding of data governance, privacy, or security fundamentals
- Contributions to open‑source projects, hackathons, or strong personal projects
- Knowledge of data visualization tools, such as Tableau or Power BI.
- You will help modernize the data and decision‑support backbone of a company that moves food at a national scale.
- You will build durable, production‑grade data foundations—trusted datasets, clear definitions, and reliable data pipelines that operate under real‑world constraints, not slideware or one‑off analyses.
- Translating complex warehouse, logistics, and operational workflows into scalable data pipelines, models, and curated datasets that support analytics and AI use cases
- Ensuring data used in daily decision‑making is accurate, timely, and resilient in environments where uptime and data quality matter
- Modernizing data ingestion, transformation, and modeling without disrupting live warehouse and transportation operations
- Location: Hybrid – Greater Philadelphia
- Reports to: IT – Data Engineering
- Salary Range: $80,000–$130,000
Preferred
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High School or better in Other
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
