Senior Data Engineer

The Hershey Company; Maharashtra; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

The Hershey Company is seeking a Senior Data Engineer in Pune, Maharashtra to design and manage enterprise-grade data products that aid analytics and reporting. This pivotal role requires an individual to develop reusable data pipelines and ensure high-quality data is accessible for analytics and AI initiatives.

Successful candidates will have extensive experience in data engineering, including strong skills in Python and SQL, and be adept in using Databricks and Azure cloud services.

Qualifications

• Strong experience with ETL/ELT design and enterprise-scale data workflows.
• Hands-on experience with Databricks and cloud data platforms like Azure.
• Proficient in Python, SQL, and source control automation.

Responsibilities

• Design, build, and maintain scalable data pipelines and transformations.
• Apply best practices for performance tuning, cost optimization, and security.
• Embed governance principles and implement data quality rules.

Skills

ETL/ELT design

Distributed processing

Python

SQL

Data modeling

Collaboration

Education

Bachelor’s/Master’s in Data Science, Engineering, or related field

Tools

Azure

Databricks

SQL-based technologies

NoSQL technologies

Job description

The Senior Data Engineer plays a critical role in designing, building, and operating enterprise‑grade data products that power analytics, reporting, and AI across Hershey’s 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.

Location: Pune, Maharashtra

This role is foundational to Hershey’s 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 Hershey’s 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 long‑lived, production‑grade assets that fuel efficiency, growth, and innovation across the enterprise.

Major Duties & Responsibilities

• Data Product Engineering & Delivery: Partner with business stakeholders to 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.
• 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 such as Delta Lake, medallion architecture, and orchestration frameworks.
• 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.
• Collaboration Across Domains: Work closely with business domain teams to validate that data products 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, and enterprise‑scale data workflows.
• Cloud & Platform Expertise: Hands‑on experience with Databricks and cloud data platforms such as Azure (preferred) or AWS, including data lakes, orchestration, and scalable compute.
• 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 building performant, 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 and Education

• Bachelor’s/Master’s in Data Science, Engineering, or a related field.
• 5–7 years 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).