Senior Manager, Data Engineering & Governance
This position is hybrid working from our Legacy West Support Center located in Plano, Texas
The Senior Manager, Data Engineering & Business Intelligence, is a hybrid player-coach role instrumental in taking new ideas in the data and artificial intelligence (AI) landscape and cultivating them into positive business outcomes. This role helps create a culture of innovation by shaping the processes needed for forward movement across the enterprise. The ideal candidate blends high-level project discovery and team leadership with hands-on technical execution. They possess strong business knowledge in a retail environment working across multiple business models (B2B, B2C, E-commerce, and brick & mortar). The candidate must have a solid, practical background in the Data and BI space 6 specifically spanning hands-on data engineering, data reporting, analytics, and data governance.
Responsibilities
Tech Delivery & Hands-On Engineering
Hands-on Development: Actively write, review, and optimize production-grade code (PySpark, SQL) to build scalable data pipelines, data architectures, and delta tables.
- Pipeline & Architecture Management: Architect and manage robust ELT/ETL processes within Azure Data Factory and optimize cloud data structures within Azure Databricks (Delta Lake, Unity Catalog).
- BI Infrastructure: Develop and govern semantic data models, advanced DAX queries, and enterprise-grade Power BI dashboards to deliver complex insights directly to business units.
- Technical Oversight: Supervise and directly contribute to the development of AI/ML models, data pipelines, and scalable data architectures, collaborating with data scientists, engineers, and product managers.
Project Discovery & Team Management
- Shepherd Leadership: Guide SMEs and business stakeholders in identifying business needs and developing problem statements, business rules, and metrics for strategic Data & AI initiatives.
- Team & Workload Leadership: Manage a high-performing team of data engineers and analysts, balancing resource allocation, mentoring technical growth, and overseeing daily Agile delivery.
- Scope & Estimation: Define and manage the overall scope of initiatives, gain appropriate signoff from stakeholders, and work across IT and vendor partners to develop timelines and cost estimates.
- Business Case Building: Assist leadership with building business cases, tracking budget-versus-actuals, and preparing for funding approvals and various stage-gating processes.
- Lifecycle Governance: Ensure requirements are met throughout the project lifecycle process and keep stakeholders apprised of changes to scope.
Stakeholder Collaboration & Partnerships
Knowledge, skills & abilities requirements
- Education: Bachelor's or Master's degree in Computer Science, Data Science, Data Engineering, or a related field, or an equivalent combination of experience, education, and training.
- Technical Stack: Advanced, hands-on experience with a modern data stack including Databricks (Spark, Delta Lake), Power BI, and Azure Data Factory (ADF).
- Experience: 8+ years of experience in a combination of data engineering, data reporting, advanced analytics, and project management.
- Leadership: 3+ years of direct people management or technical team leadership experience.
- Retail Domain: Demonstrated knowledge and experience in applying data engineering and AI to business areas within a retail environment (E-commerce, supply chain, store ops, or B2B/B2C).
- Delivery Track Record: A proven track record of managing and directly contributing code to complex data and AI programs across multiple business units.
- Communication: Skilled at creating executive-level presentations and summaries based on complex data insights.
- Methodology: Demonstrated experience with Data project life cycle processes, execution of use cases, and business benefit capture.
Competencies & attributes
- Aptitude for Innovation: Keeps up with industry trends and knowledge in the Data & AI landscape.
- Shows a Bias for Action: Proactively researches, codes, and solves complex data issues using data-driven insights.
