Data Engineer

Philip Morris India is hiring for Data Engineer.

The Data Engineer is a hands-on individual contributor responsible for designing, building and maintaining scalable data platforms, pipelines and data products that enable reliable, secure and high-quality data for analytics, reporting and AI use cases.

The role plays a critical part in establishing strong data foundations across the enterprise by developing robust ETL/ELT processes, optimizing data pipelines and ensuring data quality, governance and performance across platforms such as Snowflake and AWS.

The position bridges business requirements with technical implementation by translating data needs into efficient, production-grade data solutions that support business intelligence, advanced analytics and AI initiatives.

Responsibilities include :

1. Design, build and maintain scalable ETL/ELT pipelines using SQL, Python and tools such as Matillion, Airflow or dbt to ingest, transform and load data into enterprise data platforms.

2. Develop and optimize data models, tables and transformation logic in Snowflake to support analytics, reporting and downstream data consumption use cases.

3. Ensure efficient data ingestion and integration across multiple source systems by managing ingestion frameworks and enabling standardized data pipelines.

4. Implement data quality, validation, monitoring and recovery mechanisms to ensure accuracy, consistency and reliability of data across pipelines and data products.

5. Optimize query performance, data storage and processing efficiency through advanced SQL techniques, partitioning, indexing strategies and workload optimization.

6. Collaborate with Data Analysts, IT and business stakeholders to understand requirements and translate them into scalable data solutions supporting BI, analytics and AI use cases.

7. Define and enforce data governance policies including data security, access control, masking and lifecycle management within data platforms.

8. Support development of data products and AI/ML pipelines by enabling curated, high-quality datasets and feature-ready data layers for advanced analytics and GenAI use cases.

Work Experience :

* 8 to 10 years of experience in data engineering, data platform development or related roles, with hands-on ownership of data pipelines and data infrastructure.

* Experience working in cloud-based data environments and enterprise-scale data platforms.