Work Hours: EST (Eastern Standard Time) aligned

Experience: 6–9 years

Role Overview

We are looking for an experienced Databricks Data Engineer to support, maintain, and enhance existing Databricks-based data applications and pipelines. The role focuses on ensuring reliability, performance, and scalability of production Databricks workloads rather than building net-current platforms from scratch. You will work closely with data, analytics, and engineering teams to keep critical data applications secure, optimized, and aligned with business needs.

Key Responsibilities
Support and maintain existing Databricks applications, notebooks, jobs, and Delta Lake pipelines in production.
Monitor, troubleshoot, and resolve issues related to job failures, performance degradation, data quality, and cluster utilization.
Optimize existing Spark jobs, SQL queries, and Delta tables for cost, performance, and reliability.
Manage and improve Databricks workspace configurations, including clusters, job scheduling, access controls, and Unity Catalog (where applicable).




Implement and maintain data quality checks, logging, alerting, and basic observability for Databricks workloads.
Collaborate with stakeholders to understand requirements for enhancements or bug fixes on existing applications.
Perform incremental improvements, refactoring, and technical debt reduction on current Databricks solutions.
Ensure adherence to best practices around security, governance, and cost management within the Databricks setting.
Document existing pipelines, dependencies, and operational runbooks.
Participate in on-call or support rotations as needed to maintain production stability (within EST working hours).

Required Qualifications
6–9 years of overall experience in data engineering, with strong hands-on experience in Databricks.
Solid proficiency in Apache Spark (PySpark and/or Scala) and SQL.
Proven experience supporting and optimizing production Databricks wor

📌 Databricks Data Engineer Bengaluru (India)
🏢 Cogniify
📍 India