Job description

Role: Azure Cloud Data Engineer - Production Support Duration: Contract Location: Jersey City, NJ Client- JRI America, Inc. (a subsidiary of SMBC) Skills: Monitor, troubleshoot and support ADF pipelines and Databricks notebooks/jobs in Production. Extensive experience on Cloud solutions, specifically in Azure Experience with Azure cloud services, Azure Data Factory, Gen 2, Azure Databases, Functions, Databricks, or similar technology. Good understanding of ETL/ELT Analyze pipeline failures, spark job issues, data mismatches, cluster timeouts, resource unavailability and latency bottlenecks. Root cause analysis for incidents and outages. Understand the ADF Components and architecture. Knowledge of data integration techniques and best practices. Experience with connection to various data sources and destinations. Ability to orchestrate complex data workflows and transformation. Monitoring and troubleshooting data pipeline executions. Familiarity with ADF data flow activities for data transformations. Version control and deployment management using Azure DevOps or similar tools Awareness of ADF Integration with Azure services like Azure Data Lake Storage, Azure Databricks, etc. Skills in implementing streaming and batch data ingestion using Delta Lake. Skills in implementing data pipelines and workflows in Databricks. Familiarity with Databricks notebooks for interactive data exploration and development. Integrating Databricks with Azure Services like ADLS Gen2, Azure SQLdb. Monitoring and optimizing Databricks jobs for cost efficiency. Proficiency in Git for managing code repositories, including branching, merging and pull requests. Support CI/CD pipelines for deployment using Azure DevOps. Participate in on-call rotation and ensure business continuity via proper DR strategies. Experience with RDBS systems like Azure SQL DB, Oracle, and NoSQL Databases like MongoDB Understanding of indexing, partitioning, and other optimization techniques. Experience with stored procedure, functions, and triggers. Ensure High Availability (HA) of ADF pipelines and auto-scaling/failover readiness of Databricks clusters. Manage alerts, incidents and escalations using ServiceNow, Azure Monitor, Log Analytics etc., Proficiency in Git for managing code repositories, including branching, merging and pull requests. Experience with Confluence, ServiceNow & JIRA. Review and provide feedback on core code changes and support production deployment Knowledge on ETL DataStage Application would be a plus. Azure Monitor, Application Insights, Log Analytics. Cluster and pipeline-level metrics and logs. Required Skills/Abilities Strong hands-on experience with Azure Data Factory (ADF)- Pipeline orchestration, linked services, integration runtimes. Experience in Azure Data Bricks – running and debugging notebooks, clusters, spark job logs. Proficient in SQL – Writing/debugging queries, validating data. Good understanding of Azure Services: ADLS, Key Vault, Azure Monitor, Log Analytics. Familiarity with Azure DevOps pipelines and Git Integrations. Scripting knowledge: Python, PowerShell, or Bash. Understanding of Spark concepts and Delta Lake (Preferred). Special Requirements: Ability to work on weekends for maintenance, production implementations, recovery tests and system verifications / validations. Ability to address production issues from home outside of normal business hours..

Requirements