Databricks Developer

Job Information

Department Name

Banking

Date Opened

06/06/2026

Industry

IT Services

Job Type

Full time

Work Experience

4-5 years

Required Skills

Apache Spark

python programming

+13

City

Chennai

State/Province

Tamil Nadu

Country

India

Zip/Postal Code

600032

About Us

Kumaran Systems: Engineering Future-Ready Transformations Since 1992, Kumaran Systems has been helping enterprises bridge the past and the future, reimagining legacy systems and embracing AI-led possibilities. With over 34 years of delivery excellence, we specialise in re-engineering core applications, driving cloud transformation, and building automation-first, GenAI-enabled ecosystems across the Banking and Financial Services, Insurance, Telecom, and Automotive sectors. We help organisations not just upgrade their systems but reimagine what’s possible.

Why Kumaran?

We blend engineering discipline with AI innovation, helping clients modernise with confidence, automate with clarity, and scale with purpose. Our global delivery model ensures agility, responsiveness, and seamless collaboration, with clients always at the heart of every engagement. At Kumaran, we don’t just solve problems, we engineer future-ready transformations.

Job Description

Job Summary

We are seeking a skilled Databricks Developer to design, develop, and optimize scalable data pipelines and analytics solutions using Apache Spark, Python (PySpark), and SQL within modern cloud environments. The ideal candidate will have hands-on experience working with Databricks, Delta Lake, and cloud data platforms, and will be responsible for building high-performance data processing workflows that support data-driven decision-making.

Key Responsibilities

Pipeline Development

Design, develop, and maintain ETL/ELT data pipelines using PySpark and SQL in Databricks notebooks.

Process large-scale datasets and ensure reliable and efficient data transformations.

Architecture Design

Implement data lake and data warehouse architectures using Databricks Delta Lake and Delta Live Tables.

Build and manage Medallion Architecture (Bronze, Silver, Gold layers) for structured data processing.

Performance Optimization

Optimize Spark jobs and queries for performance, scalability, and cost-efficiency.

Manage cluster configurations, partitioning strategies, and caching mechanisms.

Cloud Integration

Integrate Databricks solutions with cloud services such as:

Azure Data Factory (ADF)

Azure Data Lake Storage (ADLS) Gen2

AWS S3 or other cloud storage platforms

Data Governance & Quality

Implement data quality checks, validation frameworks, and monitoring processes.

Ensure data security, encryption, masking, and lineage tracking.

Workflow Automation

Build and manage automated workflows and scheduling using Databricks Jobs, Airflow, or CI/CD pipelines.

Integrate with DevOps tools such as Azure DevOps or Jenkins for continuous integration and deployment.

Collaboration

Work closely with data engineers, analysts, and business stakeholders to translate business requirements into scalable data solutions.

Participate in Agile development processes including sprint planning and technical discussions.

Required Skills & Qualifications

Core Technologies

3–5+ years of experience with Databricks, Apache Spark, and Python (PySpark).

Strong experience building scalable ETL/ELT pipelines.

SQL Expertise

Advanced knowledge of Spark SQL or Databricks SQL for data transformation and analysis.

Cloud Platforms

Hands-on experience with Azure Databricks, AWS, or Google Cloud Platform (GCP).

Data Modeling

Experience with Delta Lake and Medallion Architecture (Bronze/Silver/Gold layers).

Strong understanding of data modeling and data warehouse concepts.

Version Control & CI/CD

Proficiency with Git and CI/CD tools such as Azure DevOps or Jenkins.

Preferred Qualifications

Experience with Data Build Tool (dbt).

Knowledge of workflow orchestration tools such as Apache Airflow.

Experience with Machine Learning workflows using MLflow.

Familiarity with data governance and enterprise data platforms.

Education

Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.

Key Competencies

Strong problem-solving and analytical skills

Ability to handle large-scale data processing environments

Good communication and collaboration skills in Agile teams