Data Platform Engineer

Experience

Role Overview

Data Platform Engineer

Key Responsibilities

• Design and build resilient, scalable, and high-performance data platforms.
• Work with platforms such as Databricks, Snowflake, and Kafka to develop and manage large-scale data pipelines and processing systems.
• Build and maintain applications deployed on AWS or Azure.
• Develop and optimize backend applications that are data- or computation-intensive (e.g., grid-based systems).
• Participate in code reviews, pull requests, and Agile development cycles, taking ownership across the full development lifecycle.
  

Required Skills

• 410 years of experience in data engineering and architecture.
• Hands-on expertise in Databricks, Snowflake, Kafka, AWS, and/or Azure (minimum 5 years of experience required).
• Strong programming skills in Java, Scala, or Python (with openness to learn other languages).
• Solid understanding of Object-Oriented Programming (OOP) and interest in Functional Programming concepts.
• Knowledge of data modeling, data warehousing, and distributed systems.
• Experience with tools such as Git, Bitbucket, Jenkins, JIRA, and Agile/Scrum methodologies.
• Bachelor's or Master's degree in IT, Computer Science, Engineering, or related field.
  

Preferred / Nice To Have

• Experience in financial services or knowledge of financial products.
• Prior work on grid-based computation systems or real-time data streaming platforms.
• Strong analytical and problem-solving skills.
  

Other Details

• Notice Period: Immediate to 30 days
• Work Mode: (Not specified can be adapted as per organization policy)