Manager - Operations (47438)

Business Transformation & Operations Strategy | Transmission & Distribution

DGM – Business Transformation

3–6 years

Engineering / technology; MBA preferred

Lead the digital and AI transformation of the business — owning the full journey from problem discovery and root-cause analysis, through rapid prototyping and development, to testing, rollout, adoption and measured benefit. This is the business’s technology anchor: the person teams bring an operational problem to, who determines whether digital, data or AI can solve it, and who then builds or drives the solution. A high-visibility individual-contributor role requiring equal credibility writing a prototype and presenting the case for it to leadership.

3- 6 years in digital transformation, data and analytics, technology product management, consulting or business transformation.

A portfolio of solutions actually built, deployed and in use — this weighs more than program titles.

Python and SQL; rapid prototyping with AI-assisted development and low-code tools.

Working fluency with LLMs — prompt design, agent and tool frameworks, retrieval over internal data, output evaluation.

Dashboarding — Power BI, Plotly/Dash, Streamlit or equivalent. Advanced Excel and PowerPoint.

Comfort with large, incomplete and inconsistent operational datasets.

EPC, infrastructure, power or other project-based business exposure preferred.

Learns new technology fast and independently; credible with a Project Manager on execution detail and with leadership on strategy.

Not an IT support or MIS function. The role owns business outcomes, not tickets or recurring reports.

Not an AI evangelist role. Measured on solutions in production and adopted — not awareness sessions delivered or presentations about AI.

Not a purely strategic role. Expect to build the prototype, clean the data and write the specification personally.

Not a coordination desk. The incumbent forms and defends an independent point of view, including where it is unwelcome.

A portfolio of adopted digital and AI solutions with quantified business impact; a demonstrable productivity or resource-efficiency gain traced to analytics-led intervention; AI governance defined and operating; and AI literacy raised far enough that use cases start originating from the business rather than from this role alone.