Senior Data Engineer

Job not on LinkedIn

August 29

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Logo of The Hershey Company

The Hershey Company

B2C • eCommerce • Food & Beverage

The Hershey Company is an industry-leading snacks company headquartered in Hershey, Pennsylvania, recognized for bringing goodness to the world through its iconic brands and extraordinary commitment to helping children succeed. Hershey is well-known for its wide range of chocolate and confectionery products, driven by a culture that values inclusion, employee development, and sustainable practices to ensure a positive impact on the community and the planet.

10,000+ employees

Founded 1894

👥 B2C

🛍️ eCommerce

đź’° Post-IPO Debt on 2023-04

đź“‹ Description

• ROLE OVERVIEW: Builds and optimizes platforms and systems to manage, store, and transfer data using a variety of systems. • This role will support designing, building, and maintaining robust data pipelines and infrastructure to support the company's data-driven initiatives. • This role involves transforming raw data into actionable insights by ensuring data quality, integrity, and accessibility. • The Sr. Data Engineer will collaborate with cross-functional teams to implement scalable data solutions that align with business objectives. • ACCOUNTABILITIES: Oversees systems for optimal data extraction, transformation, and loading. • Identifies, designs, and implements process improvements for scalability, data delivery optimization, and automation. • Builds advanced tools for data integration, business analytics, data cleaning/transformation, and ML/AI model deployment. • Establishes and enforces design standards and assurance processes for software, systems, and applications development. • Collaborates with stakeholders to support data infrastructure needs and resolve complex data-related technical issues. • Data Modelling Specialization: Requires extensive knowledge of database modelling techniques and concepts.

🎯 Requirements

• Data Engineering: Expertise in data manipulation, pipeline optimization, and workflow management. • Data Cleansing & Curation: Advanced skills in data cleaning, relationship identification, pattern recognition, and web scraping. • Database Modelling: Proficiency in database modelling concepts, tools, and languages. • Additional Data & Analytics Skills: Competence in descriptive and diagnostic analytics, programming, model construction, data reporting, and visualization. • Development & Coding Skills: Familiarity with ETL tools, REST APIs, data warehousing tools, modular coding, pipeline automation, and source code management. • Experience & Education: Bachelor's/Master's in Data Science, Engineering, or a related field. • 5-7 years of experience in technology. • Proficiency in one or more general-purpose programming languages (e.g., Java, C/C++, C#, Python, JavaScript). • Working knowledge of SQL-based and NoSQL technologies (e.g., PostgreSQL, MySQL, MongoDB).

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