Overview

As a Senior Engineering Manager for the Analytics Engineering team, you lead a high-performing group of engineers focused on building scalable data infrastructure, enabling advanced analytics, and driving AI-powered insights across the organization. You are responsible for technical leadership, team development, and strategic execution of data initiatives that empower product, operations, and executive teams to make informed decisions.

Responsibilities

Team Leadership & Development

• Lead, mentor, and grow a team of analytics engineers, fostering a culture of ownership, innovation, and continuous learning.
• Set clear goals, provide regular feedback, and support career development through coaching and performance management.
• Drive hiring and onboarding strategies to scale the team effectively.

Data Platform & Engineering Excellence

• Architect and oversee the development of robust, scalable data pipelines and analytics platforms using modern cloud technologies (e.g., Snowflake, dbt, Airflow, Azure).
• Ensure high data quality, reliability, and governance across all analytics systems.
• Collaborate with data science, product, and engineering teams to deliver reusable data models and metrics.

AI & Advanced Analytics Integration

• Lead the integration of AI/ML capabilities into analytics workflows, including predictive modeling, anomaly detection, and intelligent alerting.
• Partner with business stakeholders to identify high-impact AI use cases and deliver prototypes that evolve into production-grade solutions.
• Champion the use of AI tools (e.g., Microsoft Copilot, Azure ML, GitHub Copilot) to enhance engineering productivity and insight generation.

Cross-Functional Collaboration

• Act as a strategic partner to product, finance, marketing, and operations teams, translating business needs into scalable data solutions.
• Drive alignment on KPIs, data definitions, and reporting standards across departments.
• Present technical insights and recommendations to senior leadership in a clear, actionable format.

Operational Strategy & Execution

• Own the roadmap for analytics engineering, balancing short-term deliverables with long-term platform investments.
• Monitor and optimize performance, cost, and scalability of data infrastructure.
• Implement agile practices and continuous improvement processes to increase team velocity and impact.

Qualifications

8+ years of experience in data or analytics engineering, with 3+ years in a leadership role.

• Proven success in building and scaling data platforms and engineering teams.
• Strong understanding of AI/ML concepts and experience integrating them into analytics workflows.
• Expertise in SQL, Python, cloud data warehouses, and orchestration tools.
• Excellent communication and stakeholder management skills.

Preferred Skills:

• Experience with Azure Data Services, dbt, and Microsoft Copilot.
• Familiarity with data governance frameworks and compliance standards.
• Background in SaaS or customer-facing analytics environments.