Overview

Position: Senior Manager – Data Engineering

Responsibilities

• Lead and mentor a team of Data Engineers, including performance management, hiring, coaching, and career development.
• Own the design and delivery of enterprise-scale data engineering solutions.
• Architect and optimize modern data warehouse platforms with focus on performance, scalability, and cost efficiency.
• Work extensively with Snowflake for enterprise data warehousing, optimization, and cost management.
• Design and implement real-time data processing solutions using Apache Kafka and event-driven architectures.
• Build and support data lakehouse architectures using Apache Iceberg and modern table formats.
• Drive technical strategy, architecture reviews, and implementation of advanced data engineering solutions.
• Evaluate and implement modern data stack technologies and analytics platforms.
• Collaborate with senior stakeholders and cross-functional teams to align data solutions with business objectives.
• Manage complex, multi-quarter engineering initiatives across multiple teams.
• Participate in technical hiring, design reviews, and engineering best practices.
• Ensure compliance with data governance, security, and regulatory standards.

Qualifications

• About the Role
• We are seeking an experienced Senior Manager – Data Engineering to lead a talented Data Engineering team and drive the architecture, development, and delivery of enterprise-scale data solutions.
• This role requires a strong technical leader who can manage teams while remaining hands-on with architecture, coding, technical reviews, and complex engineering initiatives. You will be responsible for building scalable data platforms, driving modern data engineering practices, and enabling an AI-first analytics ecosystem.
• Bachelor’s degree in Computer Science, Data Engineering, or related technical field.
• 8+ years of experience in Data Engineering with large-scale, high-volume data environments.
• Experience managing and mentoring Data Engineering teams.
• Strong expertise in SQL optimization for large datasets and advanced Python programming.
• Extensive experience with Snowflake architecture, performance tuning, and cost optimization.
• Strong knowledge of Kimball dimensional modeling, data warehousing, and star schema design.
• Hands-on experience with AWS cloud infrastructure.
• Experience with DBT or SQLMesh for data transformation workflows.
• Strong understanding of CI/CD pipelines, GitFlow, and data engineering best practices.
• Experience implementing data governance frameworks and compliance standards such as GDPR and PCI-DSS.
• Ability to plan, prioritize, and execute engineering initiatives effectively.
• Experience collaborating with Data Analysts, Data Scientists, Machine Learning teams, and PMO functions across global teams.

Nice to have

• Experience with modern data stack technologies.
• Exposure to AI/ML-driven data platforms and analytics ecosystems.
• Strong stakeholder management and communication skills.