The Team

The Innovation & Delivery Transformation (I&DT) team is building the future of Deloitte’s business through new AI-native platforms and products. The team is responsible for identifying, nurturing, scaling, and winning in new markets through new capabilities. Rather than relying on what the firm has historically done, I&DT looks ahead and invests in areas where growth is expected three, five, and ten years into the future.

Are you looking for a unique opportunity with both start-up spirit AND enterprise strength? Deloitte’s Converge for FSI business offers both! We are looking for a talented individual with an innovative mindset to join the Converge for FSI team in our mission to develop differentiated financial services products that achieve product-market fit. This is a great opportunity to be on the frontlines of Deloitte’s innovation & product strategy while staying close to industry/sector priorities. 

Position Summary

This role is focused 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. You will lead L3 production support for AIS, working directly with client implementation teams to resolve issues they report — picking up what can't be resolved through initial triage and log review, and seeing them through to a fix. It's a hands-on technical role spanning data pipeline issues across ingestion, identity resolution, reconciliation, and publish/output failures, along with configuration troubleshooting and small enhancements, with a strong emphasis on keeping the platform reliable, accurate, and compliant as new client engagements onboard. This role is critical to the success of every implementation, since implementation teams depend on fast, accurate resolution to keep client delivery timelines on track.

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

Work you’ll do

• 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.

The successful candidate would possess these 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 written and verbal communication skills — this role sits between implementation teams and product team, translating technical root causes into clear updates for both technical and non-technical stakeholders.
• Background in investment management, asset management, or another regulated financial services domain (e.g., wealth management, insurance, banking) — familiarity with concepts like AUM, NAV, positions/transactions, or portfolio accounting is a strong plus, though not required to start.

Qualifications

Required:

• 5+ years of software engineering experience
• Ability to travel 20-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

• Experience with AWS-based data infrastructure (EMR, S3, Glue) or Snowflake, depending on the client environments this role will support.
• Experience working in a consulting or professional services delivery model, where the same platform is implemented differently across multiple external clients with distinct requirements and timelines.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $100,400 to $197,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.