Job Description

1.

Delivery Leadership & Governance:

• Own end‑to‑end delivery for Data Analytics, Data Engineering, ML/AI & GenAI programs.

• Drive delivery excellence using Agile/Scrum delivery models (aligned with DA&AI team practices).

• Establish program governance, milestones, dashboards, risk registers, quality KPIs, and SLA adherence.

• Ensure alignment with business outcomes and customer expectations.

• Manage financials including budgets, forecasting, margin optimization, and resource utilization.

• Drive continuous improvement through automation, AI infusion, and process optimization.

2.

Stakeholder & Client Management:

• Act as the primary delivery interface for customer leadership.

• Build trusted relationships by ensuring transparency, predictability, and proactive communication.

• Run cadence calls, executive reviews, and delivery health assessments.

• Work with customer teams across IT, data, and business functions to drive program value realization.

3. Technical Oversight – DA & AI

• Provide oversight across Data Engineering (ETL/ELT, Py Spark, SQL), Cloud Data Platforms, and Data Lake/Lakehouse ecosystems (Databricks, Azure/AWS/GCP).

• Guide teams working on ML/AI and GenAI use cases (LLMs, prompt engineering, model deployment, agentic AI), consistent with skills listed in internal DA&AI JDs.

• Ensure scalable architecture, code quality, data observability, and performance tuning.

• Leverage accelerators, frameworks, and best practices from DA&AI service line (e.g., WDIS, industry AI solutions).

4.

Team & Talent Management:

• Lead distributed teams across onsite/offshore models, including data engineers, data analysts, ML engineers, GenAI engineers, QA, and DevOps.

• Responsible for skill development, mentoring, performance management, and succession planning.

• Partner with Talent Acquisition to hire niche profiles in data & AI (aligned with hiring challenges highlighted in DA&AI org).

• Drive knowledge management and best‑practice institutionalization.

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