Job Purpose:
Own Americana's enterprise data platform, business intelligence and data governance end-to-end spanning data lake, ETL/ELT, semantic layer, Power BI-as-a-service and the underlying infrastructure for AI initiatives across the organization. Enable readiness to make trusted, timely, AI-ready decisions across 13 markets and 2,749+ restaurants.
Deliver the one source of truth data foundation that powers the AI Roadmap 2026-27, closes open Internal Audit commitments on Enterprise Data Catalog and metadata management, and unlocks productivity and revenue upside identified in the AI & Analytics Center of Excellence.
Key Responsibilities:
- Own and modernize Americana's enterprise data platform on Azure — data lake, warehouse, pipelines and source systems (POS, BOH, Oracle Fusion ERP, VOC, CRM, Marketing, Events, Web) delivering ≥ 99.5% pipeline reliability and ≤ 1-day exec data freshness to enable trusted decision-making across 13 markets.
- Govern and enhance the enterprise semantic layer and metric store to ensure single, consistent KPI definitions across FP&A, Ops, Marketing, HR and Customer.
- Run Power BI as an enterprise product — SLAs, adoption, cost and disciplined retirement of low-value reports — reducing the ad-hoc reporting backlogs and improving self-service maturity.
- Deliver the Enterprise Data Catalog (EDC) and comprehensive metadata management, closing Internal Audit Observations and operationalizing the Data Management SOP through Data Owner accountability, KPI validity reviews and access recertification.
- Provide the data foundation (pipeline and architecture) for the organization's AI initiatives including semantic search, RAG, observability and human-in-the-loop guardrails.
- Lead a federated team across UAE (business-facing) and Mohali (delivery bench) — building capability across data engineering, BI development, platform engineering and data governance — while driving offshoring and cost efficiency in line with FY26 org design.
- Own the platform TCO (Azure, Power BI, LLM tokens, third-party tools) with monthly ROI reporting.
- Serving key internal customers — business users needing dashboards and self-service, and the Advanced Analytics team needing production-grade ML/GenAI infrastructure.
- Player-coach leadership — comfortable in both strategy conversations and code reviews. Builds a high-performing federated data team, influences business stakeholders without direct authority, and champions automation, self-service and platform thinking over ticket-driven delivery. Demonstrated ability to say no to low-ROI reporting and to prioritise ruthlessly.
- Contributor and co-owner of enterprise data policies — Data Management SOP, data governance framework, data quality standards, semantic layer standards and Power BI publishing standards.
- Implements existing IT Security, privacy and data residency policies in partnership with IT Security and Internal Audit.
Qualification:
- Bachelor's degree in Computer Science, Engineering, Statistics or related discipline (Master's preferred).
- Preferred certifications: Azure Data Engineer Associate, DAMA CDMP, Microsoft Fabric Analytics Engineer or similar others.
Experience:
- 10–12 years of progressive experience in data engineering, BI and data platform roles, with the last 3+ years running a cloud-native lakehouse (Azure Synapse / Fabric / Databricks / Snowflake).
- Proven ownership of an enterprise Power BI deployment at scale (semantic modelling, DAX, workspace governance, capacity management).
- Hands-on delivery of data governance programs — Enterprise Data Catalog, metadata management, data quality frameworks (Purview / Collibra / Alation).
- Track record of building and leading federated / distributed teams across geographies.
- Prior exposure to QSR / Retail / CPG data landscapes.
Job Specific Skills:
- Strong Azure data stack: Data Factory, Synapse / Fabric, Data Lake, SQL, Databricks.
- Semantic layer tooling (SSAS Tabular / Fabric / dbt semantic).
- Python + SQL fluency; ability to code-review pipelines and semantic models.
- MLOps fundamentals: Azure ML, MLflow, feature stores.
- Working knowledge of LLM/GenAI patterns in a data context — RAG, semantic search, agent orchestration (LangChain / Semantic Kernel), prompt evaluation.
- Familiarity with DAMA-DMBOK and data privacy / residency requirements (UAE / KSA).
Competencies:
- Strategic Thinking: Links data platform investments to business ROI and AI roadmap outcomes.
- Influence & Communication: Explains complex data and AI concepts to executive audiences and Board forums.
- Ownership & Accountability: Owns SLAs, TCO and audit closure — bias for closure over commentary.
- Collaboration: Strong partnership with Analytics, business functions, IT Security and external partners.
- Data & Platform Expertise: Deep hands-on skills in modern data stack, semantic layer, MLOps and GenAI patterns.
- Governance Mindset: Institutionalises data quality, metadata, catalog and access recertification as recurring disciplines.
- Talent Development: Builds a high-performing federated team across UAE and Mohali.
