Senior Data Engineer
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Job Summary
Location:Pune Maharashtra
Summary
The Senior Data Engineer plays a critical role in designing building and operating enterprise grade data products that power analytics reporting and AI across Hersheys business domains. This role ensures data pipelines models and foundational components are scalable performant governed and reusable enabling consistent access to trusted data at enterprise scale.
Senior Data Engineers work closely with Data Product Managers Architects Domain SMEs and Platform Engineering to translate business requirements into robust technical solutions using modern data engineering patterns and cloud-native tooling. The role supports the end-to-end lifecycle of data products from ingestion and modeling to certification documentation and sustainable operations.
This role is foundational to Hersheys long-term data strategy. By contributing to reusable governed and durable data products the Senior Data Engineer helps establish the enterprise system of record for analytics enabling efficiency consistency and innovation across the company.
What We Are Building for Hershey
This role contributes directly to Hersheys enterprise data strategy by engineering durable reusable and governed data products that become the system of record for analytics and future AI innovation. These data products are designed to scale across domains reduce duplication increase trust and accelerate enterprise decision-making.
By applying engineering rigor governance-by-design practices and modern cloud-native architecture the Senior Data Engineer helps transition Hershey from one-off data solutions to longlived production-grade assets that fuel efficiency growth and innovation across the enterprise.
Major Duties & Responsibilities
1. Data Product Engineering & Delivery
Partner withbusiness stakeholdersto translate business requirements into technical designs and acceptance criteria.
Design build and maintain scalable and reusable data pipelines and transformations using Azure and Databricks.
Implement robust ingestion frameworks standardized patterns and repeatable workflows aligned to enterprise engineering practices.
Build and optimize physical and semantic data models supporting analytics reporting and AI/ML use cases.
2. Technical & Architectural Implementation
Apply best practices related to performance tuning cost optimization security and reliability.
Ensure alignment with enterprise architecture including shared infrastructure canonical models and platform standards.
Implement efficient data processing patterns (e.g. Delta Lake medallion architecture orchestration frameworks).
3. Governance Quality & Operations
Embed governance-by-design principles including lineage metadata documentation and certification standards.
Implement data quality rules monitoring and automated checks to ensure accuracy completeness and trust.
4. Collaboration Across Domains
Work closely with business domain teams to validatethat dataproducts meet end-user needs and match business definitions.
Partner with Platform Engineering on pipeline frameworks infrastructure patterns and optimization.
Collaborate with Data Operations & Enablement to ensure strong documentation certification and governance coverage.
Minimum Knowledge Skills and Abilities
Data Engineering & Pipelines:Strong experience with ETL/ELT design distributed processing pipeline optimization andenterprisescaledata workflows.
Cloud & Platform Expertise:Hands-on experience with Databricks and cloud data platforms such as Azure (preferred) or AWS including data lakes orchestration and scalablecompute.
Programming & Development:Proficient in Python SQL modular coding APIs source control and automation tools.
Data Modeling & Architecture:Skilled in dimensional and semantic modeling database design and buildingperformant governed analytics-ready structures.
Data Quality Metadata & Curation:Capable of cleansing transforming and validating data; familiar with lineage cataloging and data quality frameworks.
Collaboration & Communication:Able to translate business needs into technical solutions and clearly communicate technical concepts in cross-functional settings.
Experience andEducation
Bachelors/Masters in Data Science Engineering or a related field.
5 7years of experience in data analytics or engineering roles
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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The Hershey Company is an Equal Opportunity Employer. The policy of The Hershey Company is to extend opportunities to qualified applicants and employees on an equal basis regardless of an individuals race color gender age national origin religion citizenship status marital status sexual orientation gender identity transgender status physical or mental disability protected veteran status genetic information pregnancy or any other categories protected by applicable federal state or local laws.
The Hershey Company is an Equal Opportunity Employer - Minority/Female/Disabled/Protected Veterans.
You may request a reasonable accommodation if you are unable or limited in your ability to use or access our online application process as a result of a disability.
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Required Experience:
Senior IC
About Company
Here at Hershey, our purpose is to make more moments of goodness for consumers around the world.
