The Data Engineer supports, develops, and maintains data and analytics platforms
that enable reliable, scalable, and efficient access to data. This role partners
with Business and IT teams to understand requirements and leverage modern data
engineering technologies to deliver high-quality data solutions at scale. The
Data Engineer will design, develop, and maintain data pipelines and data storage
solutions, ensure data quality and integrity, and contribute to data governance,
analytics, and cloud-based data platforms. The role works within Agile delivery
environments and applies up-to-date engineering practices to continuously improve
data solutions.
Key Responsibilities
* Develop and maintain reliable, scalable, and efficient ETL/ELT data pipelines
using technologies such as Azure Databricks, PySpark, Python/Scala, and SQL.
* Design and implement data ingestion and transformation solutions for a
variety of data sources, including relational, event-based, and unstructured
data.
* Build and maintain scalable Data Lake and Lakehouse solutions and optimize
data processing and storage performance.
* Develop physical data models and implement data storage architectures in
accordance with established design and engineering guidelines.
* Implement data quality checks, monitoring, alerting, and troubleshooting
mechanisms to identify and resolve data quality and data integrity issues.
* Analyze complex data elements, data flows, dependencies, and relationships to
contribute to conceptual, logical, and physical data models.
* Develop and operate large-scale data storage and processing solutions using
distributed and cloud-based technologies.
* Work with Azure services such as Azure Data Lake Storage (ADLS), Event Hubs,
and Azure Functions to support scalable data solutions.
* Implement and support data governance practices, including metadata
management, data access, retention, and availability.
* Participate in testing, validation, troubleshooting, and continuous
improvement of
📌 Data Engineer (Pune)
🏢 Cummins
📍 Pune