Senior Data Engineer

Hershey Company; Pune District; On-site; INR 3,000,000 - 4,600,000; Full time

Job summary

The Hershey Company in Pune, India seeks a Senior Data Engineer to design, build, and operate enterprise-grade data products powering analytics and AI across business domains. You will ensure scalable, governed data pipelines and models delivering trusted data at enterprise scale.

Collaborate with stakeholders to translate requirements into technical designs, develop data pipelines using Azure and Databricks, and implement governance, data quality, and scalable data models for analytics and

Qualifications

• 5–7 years of experience in data, analytics, or engineering roles.
• Proficient in ETL/ELT, distributed processing, and enterprise-scale data workflows.
• Hands-on Databricks and cloud data platforms (Azure preferred).
• Strong with Python, SQL, APIs, source control, and automation tools.
• Experience with dimensional/semantic data modeling, data quality, and governance.

Responsibilities

• Translate business requirements into technical designs and acceptance criteria.
• Design, build, and maintain scalable data pipelines and transformations using Azure and Databricks.
• Implement robust ingestion frameworks and repeatable workflows.
• Develop physical and semantic data models for analytics and AI/ML use cases.
• Apply performance tuning, cost optimization, security, and reliability best practices.
• Ensure alignment with enterprise architecture and platform standards.
• Embed governance-by-design: lineage, metadata, documentation, and certification.
• Implement data quality rules, monitoring, and automated checks for trust.
• Collaborate with domain teams to meet end-user needs and definitions.
• Partner with Platform Engineering on pipelines, patterns, and optimization.
• Work with Data Operations to ensure documentation and governance coverage.

Skills

ETL/ELT design

Databricks

Azure

Python

SQL

APIs

Source control

Automation tools

Data modeling

Data quality

Governance

Education

Bachelor’s/Master’s in Data Science/Engineering

Tools

Databricks

Azure

AWS

PostgreSQL

MySQL

MongoDB

Job description

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 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.

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

• 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.
• 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.
• 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.
• 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

• Strong experience with ETL/ELT design, distributed processing, pipeline optimization, and enterprise‑scale data workflows.
• Hands‑on experience with Databricks and cloud data platforms such as Azure (preferred) or AWS, including data lakes, orchestration, and scalable compute.
• Proficient in Python, SQL, modular coding, APIs, source control, and automation tools.
• Skilled in dimensional and semantic modeling, database design, and building performant, governed analytics‑ready structures.
• Capable of cleansing, transforming, and validating data; familiar with lineage, cataloging, and data quality frameworks.
• 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.
• Working knowledge of SQL‑based and NoSQL technologies (e.g., PostgreSQL, MySQL, MongoDB).