Cloud Data Specialist (Azure) - Vice President

Sumitomo Mitsui Banking Corporation•Charlotte, NC

73d•Hybrid

About The Position

SMBC is looking for a Azure Cloud Data Engineer in the Production Support group with a strong Azure DataFactory and Databricks knowledge. Candidate should be able to provide support for Azure based data integration and analytics pipelines built using Azure Data Factory and Azure Databricks ensuring the uptime and performance of critical pipelines and workflows. This role should also have knowledge of complex interface process development and is required to troubleshoot issues.

Requirements

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).
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.

Nice To Haves

Knowledge on ETL DataStage Application would be a plus.

Responsibilities

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
Azure Monitor, Application Insights, Log Analytics.
Cluster and pipeline-level metrics and logs.