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Job Description & How to Apply Below
Why Mizuho
At Mizuho, we provide the stability of an international industry leader with the career trajectory of a growing business. Our steady, strategic growth gives our people at all levels rewarding degrees of responsibility and richer work experience than a boutique firm or an established giant could offer alone.
It’s the local expertise of our employees that makes our global network so powerful. By collaborating with colleagues and clients who share the same ambition and drive, you can amplify your sphere of influence and base of knowledge as part of one of the largest banks in the world.
We are seeking a highly skilled and motivated Data Analytics L2 Support Engineer to join our production support team. The ideal candidate will be responsible for providing Level 2 support for data analytics and business intelligence platforms, with a strong focus on incident management, production stability, and operational excellence across reporting, semantic models, and analytics solutions.
In addition to core L2 support responsibilities, this role operates within the Analytics Center of Acceleration (COA) model, supporting not only production stability but also contributing to continuous improvement, platform scalability, and BAU (Business-as-Usual) analytics development activities. The engineer will play a dual role in ensuring system reliability while enabling incremental enhancements, small feature builds, and optimization of existing analytics solutions aligned with COA standards.
This role is centered on hands-on L2 production support, including monitoring scheduled and batch jobs, reviewing job execution statuses, and troubleshooting failures across ETL pipelines, data warehouses, and reporting layers. The engineer will act as a key escalation point for L1 support, performing root cause analysis, implementing temporary and permanent fixes, and coordinating with engineering, infrastructure, and vendor teams to resolve production incidents within defined SLAs.
The Data Analytics L2 Support Engineer will also handle intraday user inquiries, investigate data quality and reporting discrepancies, and validate data corrections before and after production deployments. A strong understanding of data warehousing concepts, ETL processes, and analytics workflows is essential. Experience supporting business intelligence tools—particularly Power BI—in a production environment is required.
This position requires close collaboration with U.S.
-based business users, business analysts, and development teams, working across time zones from an India-based support location to translate business-reported issues into technical diagnoses and clearly communicate status, impact, and resolution. Strong analytical thinking, attention to detail, and the ability to operate effectively in a high-availability, production support environment are critical for success.
Key Platform and Technology Expertise
Snowflake cloud data platform
Power BI reporting and analytics
Enterprise job scheduling tools (ie. Tidal)
Power BI Report Scheduler (PBRS)
Microsoft SQL Server
Enterprise data warehousing concepts and architectures
Semantic model development and tooling (ie. Cube Dev)
Key Responsibilities:
Own Level 2 incident management for enterprise data analytics platforms, ensuring timely diagnosis, containment, and resolution of production issues in accordance with SLA and regulatory expectations.
Perform deep technical triage and root cause analysis of recurring and high‑severity incidents across data ingestion, transformation, semantic models, and reporting layers.
Drive problem management activities, including trend analysis, identification of systemic weaknesses, and implementation of preventative controls to improve platform stability.
Monitor and govern batch, scheduled, and intraday analytics workloads, ensuring successful completion of critical financial reporting and downstream dependencies.
Execute controlled data remediation and validation activities, ensuring accuracy, reconciliation, and auditability of corrected data in production environments.
Partner with development and infrastructure teams to design and implement permanent fixes,…
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