Senior Data Engineer

Role & responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks (Spark / PySpark)
• Orchestrate and monitor workflows using Apache Airflow for batch and incremental processing
• Build and optimize ELT pipelines in Snowflake, ensuring performance, reliability, and cost efficiency
• Develop production-quality Python code for data processing, transformations, and integrations
• Design, build, and host APIs and data services using modern Python frameworks
• Deploy and manage APIs using Azure-native services (Azure Functions, App Services, API Management)
• Apply Azure cloud best practices for security, scalability, monitoring, resiliency, and cost optimization
• Implement data quality checks, logging, alerting, and observability for production pipelines
• Collaborate with analytics, product, and platform teams to enable downstream data consumption
• Participate in architecture design, code reviews, and technical decision-making
• Troubleshoot and resolve complex production issues across data pipelines and cloud infrastructure
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Preferred candidate profile

• B.Tech. / MCA / Graduation
• 4+ years of total experience
• Solid hands-on experience with Databricks (Spark / PySpark) in production environments
• Experience building and hosting REST APIs / data services using Python frameworks
• Solid experience with Microsoft Azure, including cloud-native architecture and best practices
• Solid working experience with Snowflake, including data modeling and performance tuning
• Solid understanding of data warehousing, ELT patterns, and modern cloud data architecture
• Proven expertise with Apache Airflow for workflow orchestration and dependency management
• Proven advanced Python programming skills for data engineering and API development
• Demonstrated ability to independently own, design, and deliver end-to-end data engineering solutions

Preferred Qualification:

• Experience with CI/CD pipelines, Git-based version control, and deployment automation
• Good Knowledge of SQL, Pyspark, Snowflake cloud tech stacks, python, exposure in code management, AI usage to add efficiency.