Responsibilities:

Oversee daily data loads and ensure the smooth operation of data pipelines and related systems.
Troubleshoot and resolve issues such as pipeline failures, performance bottlenecks, schema mismatches, and cloud resource disruptions.
Conduct root-cause analyses and implement permanent solutions to prevent recurring issues.
Maintain and optimize existing data processes, refactoring or retiring outdated workflows as necessary.
Design and build scalable data ingestion pipelines using technologies such as Azure Data Factory, Databricks, and Synapse Pipelines.
Collaborate with teams to create and improve operational runbooks, monitoring dashboards, and incident response workflows.
Develop reusable ingestion patterns for platforms like Guidewire DataHub, InfoCenter, and other business data sources.
Lead the implementation of real-time and event-driven data engineering solutions to enable operational insights and automation.
Partner with architects to modernize data workloads using advanced frameworks like Delta Lake and Medallion Architecture.
Mentor entry-level engineers, enforce coding best practices, and review code to ensure quality and compliance. Requirements
Expertise in ETL processes and tools for efficient data extraction, transformation, and loading.
Proficiency in Microsoft SQL Server for database programming and management.
Hands-on experience with Azure technologies such as Data Factory, Data Lake, and Databricks.
Strong scripting skills in T-SQL and PL/SQL for database optimization.
Familiarity with real-time data processing and event-driven architectures.
Knowledge of modern data governance practices and tools.
Ability to create analytics-ready datasets that support advanced reporting and insights.
Strong leadership and communication skills to guide teams and collaborate across departments.

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