Job Description

Key Responsibilities :

Monitor, maintain, and support enterprise data platforms and production environments.
Build, manage, and troubleshoot data pipelines using Databricks and Spark.
Handle production incidents, perform root cause analysis (RCA), and ensure timely issue resolution.
Develop and maintain data workflows using Airflow.
Work with Azure services and Unity Catalog to manage enterprise data solutions.
Collaborate with cross-functional teams to ensure data quality, platform reliability, and operational excellence.
Participate in on-call support and production maintenance activities.
Prepare technical documentation and support continuous platform improvements.

Required Skills

5 - 8 years of experience in Data Engineering and DataOps.




Minimum 3 years of hands-on experience in Data Production Support and Incident Management.
Solid expertise in :
Python
Databricks
Unity Catalog
ADLS (Azure Data Lake Storage)
Apache Spark
Apache Airflow
Data Pipeline Architecture & Design
Azure Services (Kubernetes, AVD, Log Analytics Workspace, Azure SQL, Cost Management)
Troubleshooting & Root Cause Analysis (RCA)
Incident Management
Stakeholder Management
Excellent communication and analytical skills.

Good To Have

Terraform
Kubernetes
Power BI
GitLab
Shell Scripting
Jira & Confluence
Feature Leadership experience

(ref:hirist.tech)

📌 Coffeebeans.io - Data Support Engineer (Chennai)
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