Join Kumaran Systems as a Senior Databricks Developer. Design and implement scalable data engineering solutions using Databricks and Apache Spark in a dynamic IT services environment.

About the Company

Kumaran Systems, an IT services company established in 1992, specializes in engineering future-ready transformations. With over three decades of delivery excellence, the firm reimagines legacy systems and embraces AI-led possibilities across Banking and Financial Services, Insurance, Telecom, and Automotive sectors. Their core expertise lies in re-engineering core applications, driving cloud transformation, and building automation-first, GenAI-enabled ecosystems. The company blends engineering discipline with AI innovation, enabling clients to modernize with confidence, automate with clarity, and scale with purpose. A global delivery model ensures agility, responsiveness, and seamless collaboration.

Role Overview

We are seeking an experienced Senior Databricks Developer with 5+ years of experience in designing and implementing scalable data engineering solutions. The ideal candidate will possess strong expertise in big data processing, data pipeline development, and cloud-based data platforms, with hands-on experience using Databricks and distributed data processing frameworks like Apache Spark. This role involves building robust data pipelines, optimizing large-scale data processing workloads, and collaborating with data engineers, analysts, and business stakeholders to enable data-driven decision-making.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks.
• Build and optimize large-scale data processing solutions using Apache Spark.
• Develop and manage ETL/ELT workflows for ingesting, transforming, and processing structured and unstructured data.
• Write efficient data processing scripts using Python, Scala, and SQL.
• Implement and manage data lake and data warehouse architectures.
• Optimize performance of data pipelines and Spark jobs.
• Integrate Databricks with cloud data services and storage platforms.
• Collaborate with data scientists, analysts, and engineering teams to deliver reliable data solutions.
• Implement best practices for data governance, data quality, and security.
• Troubleshoot data pipeline issues and ensure system reliability and scalability.
• Document data architecture, workflows, and operational processes.

Tech Stack

• Primary Platform: Databricks
• Data Processing: Apache Spark
• Languages: Python, Scala, SQL
• ETL/ELT Frameworks: Custom ETL/ELT pipelines
• Cloud Platforms: Microsoft Azure, Amazon Web Services, Google Cloud Platform
• Data Architecture: Data Lake, Data Warehouse, Data Modeling

5+ years in data engineering or big data development; strong Hands-on Databricks; extensive experience with Apache Spark; proficiency in Python, Scala, SQL; building scalable ETL/ELT pipelines; working with large datasets in data lake/warehouse environments; experience with Azure, AWS, or GCP; strong knowledge of data modeling, data architecture, data integration concepts; excellent analytical, troubleshooting, performance optimization skills; experience in Banking/Financial Services preferred; 4-5 years overall experience.

Not specified