Sumitomo Mitsui Banking Corporation-posted 12 days ago
Full-time • Mid Level
Charlotte, NC
5,001-10,000 employees

The Data Support Engineer ensures the reliability, performance, and integrity of compliance and analytics data platforms within a cloud-based ecosystem. This role anchors operational excellence by supporting trade and market surveillance, compliance metrics, and analytics dashboards. It impacts business-critical reporting and regulatory adherence, influencing risk management and decision-making across the organization. The position reports to the Compliance Technology Manager and collaborates with cross-functional teams under Agile/Scrum frameworks using Jira and Confluence.

  • Monitor, troubleshoot, and resolve issues in compliance and analytics data pipelines to meet SLAs.
  • Perform root cause analysis for data quality and integrity issues and implement corrective actions.
  • Provide operational support for analytics dashboards and reporting tools, ensuring data consistency across compliance and analytics layers.
  • Takes initiative to proactively anticipate challenges and drive solutions before issues arise.
  • Manage run-time integration and orchestration between Azure Databricks and Azure Data Factory, including configuration of linked services, triggers, and pipelines.
  • Support data solutions leveraging Medallion architecture to ensure structured, scalable, and secure data layers. Maintain and optimize workflows in Databricks, Azure Data Factory (ADF), and Azure SQL Database for performance, scalability, and cost efficiency.
  • Support deployment and configuration of data solutions in production environments.
  • Document operational procedures and troubleshooting steps in Confluence; track tasks and issues in Jira.
  • Ensure adherence to data governance, security, and regulatory standards; assist in compliance audits and reporting processes.
  • Demonstrates flexibility to perform diverse functions within the team to address organizational needs
  • Minimum 3 years in data operations, support engineering, or analytics platform administration.
  • Proficiency in Medallion architecture, Azure Databricks, Azure Data Factory, Azure SQL Database, and orchestration between Databricks and ADF.
  • Ability to query and analyze large datasets for troubleshooting and validation.
  • Hands-on experience with Jira and Confluence; familiarity with Agile/Scrum methodologies.
  • Strong problem-solving, communication, and collaboration abilities.
  • Python or PySpark for automation
  • knowledge of compliance or financial services workflows
  • exposure to visualization tools (Power BI, Tableau)
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