ConvergeProsperity - Production Support Lead - Innovation_Delivery_Transformation

About the role

The Innovation & Delivery Transformation (I&DT) team is building the future of Deloitte's business through new AI-native platforms and products. The team identifies, nurtures, scales, and wins in new markets through new capabilities, looking ahead to invest in areas where growth is expected three, five, and ten years into the future. Deloitte's Converge for FSI business offers both start‑up spirit and enterprise strength, seeking a talented individual with an innovative mindset to develop differentiated financial services products that achieve product‑market fit. This role provides a front‑line view of Deloitte's innovation and product strategy while staying aligned with industry and sector priorities.

Position Summary: This role focuses on Asset Insight Suite (AIS), Deloitte's data platform for investment management. As the Production Support Lead, you will be part of the AIS product and engineering team, leading L3 production support for AIS. You will work directly with client implementation teams to resolve issues they report, picking up what cannot be resolved through initial triage and log review and seeing them through to a fix. The role is hands‑on, covering data pipeline issues across ingestion, identity resolution, reconciliation, and publish/output failures, plus configuration troubleshooting and small enhancements, with a strong emphasis on keeping the platform reliable, accurate, and compliant as new client engagements onboard. Fast, accurate resolution is critical to implementation success, as teams depend on it to keep client delivery timelines on track.

Recruiting for this role ends on 10/31/26.

Responsibilities

• Own L3 triage and resolution for issues reported directly by client implementation teams, spanning the full AIS pipeline.
• Diagnose data pipeline failures using the ABC (Audit, Balance, Control) framework - tracing a failed, delayed, or incorrect event, and run status to identify where in the pipeline a job stalled, failed, or produced unexpected output.
• Troubleshoot identity-resolution issues reported during implementation - working with the implementation team to determine whether the root cause is a data pipeline configuration issue, a source data quality issue, or a platform defect.
• Perform root-cause analysis on issues reported during onboarding and steady-state runs, document findings clearly for the implementation team, and implement fixes - the majority of which are config corrections (AIS is config-driven by design), with a smaller share requiring code changes in the PySpark/Snowpark pipeline.
• Act as the technical point of contact for implementation teams during active client onboarding, answering config-behavior questions, validating that new source feeds are mapping correctly through medallion architecture, and confirming data product outputs match what was specified for that client.
• Monitor platform health and