Lead Commercial Data Intelligence Analyst

Key Responsibilities

• Data Strategy & Leadership Own and advance the commercial data strategy, ensuring a single source of truth for reporting, analytics, and AI/ML initiatives. Provide strategic directions for data integration and management.
• Team Leadership & Mentorship Lead, mentor, and develop a team of Commercial Data Intelligence Analysts. Drive best practices in data modeling, pipeline development, and AI-ready data preparation.
• Data Engineering Oversight Oversee the design, implementation, and maintenance of scalable ETL/ELT pipelines using Microsoft-based tools (e.g., Data Factory, Synapse, Fabric pipelines). Ensure adoption of standardized data infrastructure, replacing non-standard sources with governed datasets.
• AI & Advanced Analytics Enablement Partner with business and analytics teams to prepare structured, clean, and enriched datasets for machine learning, predictive modeling, and recommendation engines. Support feature engineering and model deployment.
• Stakeholder Engagement & Advisory Collaborate with senior leaders across commercial, sales, and operations functions to define data requirements, design analytical solutions, and ensure alignment with business objectives. Act as a trusted advisor for data-driven decision-making.
• Data Quality & Continuous Improvement Establish standards for data quality, governance, and validation. Identify opportunities to improve data workflows, streamline processes, and enhance dataset reliability. Stay current with Microsoft Fabric, cloud data engineering trends, and AI/ML best practices.
• SQL & Data Architecture Oversee the development of complex SQL queries, data models, and integration pipelines to support scalable analytics, AI workflows, and operational reporting.

Skills & Qualifications

• Bachelors or masters degree in data engineering, Computer Science, Information Systems, or related field.
• 10+ years of experience in data integration, engineering, or commercial data management roles, with at least 2 years in a leadership capacity.
• Strong expertise in SQL, data modeling, ETL/ELT pipelines, and cloud-based platforms (Azure Synapse, Microsoft Fabric, Databricks, or similar).
• Proven experience in leading teams to deliver AI/ML-ready datasets and analytics solutions.
• Knowledge of data governance, quality frameworks, and commercial system data structures (e.g., Salesforce).
• Excellent problem-solving skills, with a strong focus on data accuracy, integrity, and usability.
• Outstanding communication and collaboration skills, with experience engaging senior stakeholders and cross-functional teams.