Senior Manager - Data Engineering, Business Intelligence & Data Governance

Overview

This leadership role entails end-to-end stewardship of Americana's enterprise data platform, encompassing data lakes, ETL/ELT pipelines, semantic layers, Power BI service, and supporting infrastructure for AI across 13 markets and over 2,749 restaurants. The position aims to establish a trusted and current data foundation driving the AI Roadmap 2026-27, fulfilling internal audit data obligations, and unlocking business value through analytics.

Key Responsibilities

• Lead modernization and management of the Azure-based enterprise data platform including data lake, warehouse, pipelines, and integrating multiple source systems such as POS, ERP, CRM, and marketing tools ensuring at least 99.5% pipeline uptime and executive data freshness within one day.
• Oversee enterprise semantic layers and maintain a consistent metric repository to guarantee unified KPI definitions across departments like FP&A, Operations, Marketing, HR, and Customer Experience.
• Administer Power BI as a company-wide product ensuring service level agreements, driving adoption, managing costs, and phasing out redundant reports to reduce backlog and enhance self-service analytics capabilities.
• Implement and administrate an Enterprise Data Catalog and metadata framework to close internal audit findings and operationalize data governance practices including Data Owner responsibilities, KPI reviews, and access recertification.
• Develop the data pipelines and architecture that underpin AI projects including semantic search, retrieval augmented generation, observability, and human-in-the-loop control mechanisms.
• Lead a distributed team with both business-facing members in UAE and technical staff in Mohali, fostering capabilities in data engineering, BI development, platform operations, and governance while optimizing offshore resources and organizational efficiency.
• Manage total cost of ownership of the data platform including Azure infrastructure, Power BI licensing, AI token consumption, and third-party tools with monthly ROI monitoring.
• Engage with internal customers ranging from business users requiring dashboards to advanced analytics teams needing production-grade machine learning and generative AI infrastructure.
• Exhibit strong player-coach leadership balancing strategic discussion and technical reviews, influencing stakeholders without direct authority, and promoting automation and platform-centric solutions instead of ad hoc ticket responses. Prioritize high-value initiatives and decisively decline low-ROI requests.
• Contribute to and co-own enterprise-wide policies for data management, governance frameworks, quality standards, semantic layer protocols, and Power BI publishing guidelines.
• Ensure adherence to IT security policies, data privacy, and residency requirements by collaborating with IT security and internal audit departments.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics, or related fields; Master's preferred.
• Certifications such as Azure Data Engineer Associate, DAMA CDMP, Microsoft Fabric Analytics Engineer, or equivalents are advantageous.

Experience

• 10 to 12 years of progressive experience in data engineering, BI, and platform management with minimum 3 years managing cloud-native lakehouse solutions like Azure Synapse, Fabric, Databricks, or Snowflake.
• Proven track record managing large scale enterprise Power BI deployments, including semantic modeling, DAX, workspace governance, and capacity planning.
• Hands-on experience delivering data governance programs involving Enterprise Data Catalogs, metadata management, and data quality frameworks using tools such as Purview, Collibra, or Alation.
• Experience building and leading distributed teams across multiple locations.
• Familiarity with data ecosystems of Quick Service Restaurants, Retail, or Consumer Packaged Goods sectors.

Technical Skills

• Deep expertise in Azure data technologies: Data Factory, Synapse/Fabric, Data Lake, SQL, Databricks.
• Familiarity with semantic layer tools like SSAS Tabular, Fabric, or dbt semantic.
• Proficient in Python and SQL including capability to conduct code reviews of data pipelines and semantic models.
• Understanding of MLOps fundamentals including Azure ML, MLflow, and feature stores.
• Knowledge of Large Language Models and generative AI applications in data contexts such as retrieval augmented generation, semantic search, agent orchestration with frameworks like LangChain or Semantic Kernel, and prompt evaluation.
• Awareness of Data Management Body of Knowledge (DAMA-DMBOK) and regional data privacy and residency mandates (UAE and KSA).

Core Competencies

• Strategic alignment of data platform investments with business outcomes and AI roadmap targets.
• Ability to clearly communicate complex data and AI insights to executives and board members.
• Strong sense of ownership overseeing service levels, platform costs, and audit compliance with a focus on deliverables.
• Collaborative mindset partnering effectively across analytics, business units, IT security, and external stakeholders.
• Technical mastery of modern data stacks, semantic layers, machine learning operations, and generative AI methodologies.
• Firm governance orientation ensuring data quality, metadata accuracy, catalog completeness, and regular access reviews.
• Leadership in talent development cultivating a high-functioning federated team across UAE and India.