Join our team as a Senior Data Engineer to tackle complex data challenges using modern cloud technologies like Databricks, Snowflake, and Azure.

About the Company

Our mission is to drive innovation through cutting-edge data solutions. We tackle some of the toughest data challenges that organizations face today, providing the tools and strategies needed to thrive in a digital-first world. Our collaborative environment fosters creativity and encourages our team to take ownership of their work while continuously learning and growing.

Role Overview

We are seeking a dedicated and experienced Senior Data Engineer specialized in ETL processes to join our team. This is a hybrid role based in Pune, India, and you will play a crucial part in building and optimizing our data infrastructure that supports analytics, reporting, and advanced AI applications. We are looking for someone who is passionate about data engineering and has a profound understanding of modern technologies and frameworks.

Key Responsibilities

• Design and develop scalable ETL/ELT pipelines for enterprise data platforms, ensuring high performance and reliability.
• Build and optimize solutions utilizing Apache Spark, Azure Databricks, and Snowflake to enable data access and insights.
• Create integration workflows using Azure Functions, as well as manage the flow of data with Azure Service Bus.
• Develop complex SQL transformations and data models to meet the analytic needs of the organization.
• Implement Infrastructure-as-Code methodologies using Terraform to streamline operations and improve deployment efficiencies.
• Construct and maintain Continuous Integration/Continuous Deployment (CI/CD) pipelines to enhance code quality and automate deployments.
• Collaborate with cross-functional teams including analytics, business, and engineering to formulate and deliver impactful data solutions.
• Ensure data quality, scalability, reliability, and security across all data platforms involved.

Tech Stack

• Languages & Databases: Python, SQL, Snowflake
• Data Processing: Apache Spark (PySpark, Spark SQL), Azure Databricks (Unity Catalog)
• Cloud Services: Azure Functions, Azure Service Bus
• DevOps Tools: Terraform, GitHub Actions, Git, Artifactory, SonarQube

• 7–8 years of experience in Data Engineering and ETL/ELT processes.
• Proficient in Python and Advanced SQL.
• Hands-on experience with Apache Spark (PySpark, Spark SQL).
• Expertise in Azure Databricks (Unity Catalog).
• Familiarity with Snowflake for data warehousing.
• Knowledge of Azure Functions and Azure Service Bus.
• Experience with Infrastructure-as-Code practices using Terraform.
• Understanding of CI/CD pipelines with GitHub Actions, Git, Artifactory, SonarQube.
• Familiarity with DevOps practices is essential.

Nice to Have:

• Experience with AI/ML initiatives and exposure to Large Language Models (LLMs).
• Knowledge of Data Platform Architecture and Performance Optimization.
• Cloud-Native Data Engineering expertise.

• Opportunity to work on enterprise-scale data platforms and modern cloud technologies.
• Be a part of exciting analytics and AI-driven initiatives.
• Collaborate with talented teams and industry experts.
• Solve meaningful challenges and make a real business impact.
• Grow your career in an environment that values innovation, ownership, and continuous learning.