We are looking for a Data Engineer (Support) with strong expertise in the Microsoft Azure Cloud ecosystem to ensure the smooth operation, reliability, and scalability of our data infrastructure. This role will focus on monitoring, troubleshooting, and optimizing data pipelines and Azure data services while collaborating with data teams to support analytics and business intelligence functions.This role requires a strong understanding of cloud data architecture, hands-on experience with Azure data services (including Microsoft Fabric), and deep practical knowledge of Databricks for batch and data engineering. This Data Engineer role will focus on cloud infrastructure, data pipelines, and analytics support within the Azure ecosystem.
Key Responsibilities

• Provide production support for Azure-based data pipelines, data lakes, and data warehouses.
• Monitor and resolve data ingestion, transformation, and performance issues across Azure Data Factory, Databricks, Synapse, and other services.
• Manage and troubleshoot ETL/ELT processes, ensuring data reliability and availability.
• Implement and maintain data quality checks, validation frameworks, and alerting systems.
• Collaborate with data engineers and business teams to analyze and fix data discrepancies.
• Develop scripts or automation tools using Python or PowerShell to improve operational efficiency.
• Participate in on-call rotations for incident management and escalation support.
• Maintain detailed documentation of data workflows, configurations, and incident resolutions.
• Suggest and implement process improvements to enhance reliability and reduce manual interventions.

Eligibility / Qualification Required:

Required Skills and Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or related field.
• 3+ years of experience in data engineering, data platform operations, or production support.
• Strong expertise in Microsoft Azure Cloud, including:
  • Azure Data Factory (ADF)
  • Azure Synapse Analytics
  • Azure Databricks
  • Azure Data Lake Storage (ADLS)
  • Azure Monitor / Log Analytics / Application Insights
• Proficiency in SQL for querying and debugging data issues.
• Experience with Python or PowerShell for automation and data processing.
• Familiarity with DevOps tools (Azure DevOps, Git, CI/CD pipelines).
• Understanding of data modeling, ETL concepts, and data warehousing principles.
• Strong problem-solving, communication, and incident management skills.

Preferred Qualifications

• Azure certifications such as:
  • Microsoft Certified: Azure Data Engineer Associate (DP-203)
  • Azure Administrator Associate (AZ-104)
• Experience with Databricks job orchestration, Delta Lake, or Spark.
• Familiarity with ITIL processes or structured incident/change management frameworks.
• Experience supporting real-time data streaming using Azure Event Hubs or Kafka.

How to Apply:

Please refer to the original job posting for application details.

General Conditions:

No general conditions were specified in the provided text.
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