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 growth expected three, five, and ten years into the future. Deloitte's Converge for FSI business offers a unique opportunity with start‑up spirit and enterprise strength. As the Production Support Lead for the Asset Insight Suite (AIS), you will be part of the AIS product and engineering team, leading L3 production support, working directly with client implementation teams to resolve issues, ensuring platform reliability, accuracy, and compliance as new client engagements onboard.

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 reliability, including SLA adherence and event success rates, proactively flagging patterns that could affect multiple implementations before they're individually reported.
• Maintain and improve runbooks, config troubleshooting guides, and known‑issue documentation based on recurring implementation‑team questions, reducing repeat escalations over time.
• Support security and compliance posture – investigating and remediating access‑control issues (RBAC, per‑client/per‑source data scoping) reported during implementation, and ensuring resolution meets audit expectations for a platform handling client‑confidential financial data.
• Implement small config‑based enhancements requested by implementation teams during onboarding, working within established config patterns rather than requiring new engine development from platform engineering.
• Participate in an on‑call/coverage rotation to support active implementations, with clear escalation paths to platform engineering for issues requiring deeper architectural changes.

Skills

• Strong SQL and data debugging skills – comfortable tracing an issue through multi‑layer data pipelines and long‑format (key‑value) data models, not just traditional wide‑format tables.
• Working knowledge of PySpark and/or Snowpark; Python proficiency for writing fixes, scripts, and diagnostic tooling.
• Familiarity with AWS services relevant to the platform (EMR, S3, Glue) and/or Snowflake, depending on client deployment.
• Experience with production support/incident management practices – triage, root‑cause analysis, clear documentation, and escalation discipline – ideally in a regulated or financial‑services environment.
• Understanding of data lineage, audit, and identity‑resolution concepts (or strong willingness/ability to learn AIS's specific model quickly) – since most production issues trace back to a source, event identifier mismatch rather than application logic.
• Comfort working directly with client‑facing implementation teams under delivery timeline pressure – this role needs someone who communicates clearly and stays calm when an onboarding deadline is at risk.
• Working knowledge of general security practices for systems handling sensitive client and financial data.
• Strong