Manager, Data & Analytics Engineering - 11513

What You'll Do:

Team Leadership & Development
Lead, mentor, and grow a team of data and analytics engineers, fostering a collaborative, high-performance culture focused on continuous improvement.
Provide technical direction, career development support, and hands-on guidance to ensure team excellence and individual growth.
Drive hiring and onboarding to scale the team in alignment with organizational growth and evolving business needs.
Establish clear performance expectations and delivery standards, ensuring accountability and quality across the team.
Coordinate effectively across time zones and geographies as the team composition evolves.
Data Curation & Model Development
Own the curation, transformation, and delivery of analytics-ready data models supporting Product and Customer Value use cases.
Champion dbt best practices including modular design, rigorous testing, comprehensive documentation, and governance tagging to ensure all models meet certification standards.
Collaborate with data architects and upstream data engineering teams to ensure source data quality and alignment with downstream modeling needs.
Build and maintain trusted, governed data assets that serve as a single source of truth for BI and analytics consumers.
Institutionalize engineering standards for code reviews, CI/CD, monitoring, and proactive incident management within the team.
BI Delivery & Analytics Enablement
Oversee the development and delivery of Tableau and Sigma dashboards that meet business requirements and enhance stakeholder decision-making.
Ensure data models are optimized for downstream visualization, enabling effective governed self-service analytics.
Translate complex business requirements from Product and Customer Value stakeholders into well-structured data solutions and BI deliverables.
Support governance and data integrity across all analytics processes, ensuring adherence to organizational data standards and access controls.
Stakeholder Partnership & Communication
Build and maintain strong relationships with Product and Customer Value leadership, acting as a trusted partner for data-driven decision-making.
Communicate technical roadmaps, risks, trade-offs, and delivery timelines clearly to both technical and non-technical audiences.
Evangelize a data-driven culture by ensuring data assets are discoverable, well-documented, and championed across the teams you support.
Collaborate cross-functionally with other data engineering teams, data governance, and platform teams to ensure alignment and consistency.

What You Will Bring to Coupa:

• Experience: 6+ years in Data/Analytics Engineering, with demonstrated ability to lead technical projects and guide other engineers.
• Modern Stack Expertise: Strong hands-on proficiency with SQL, dbt, and cloud data warehouses (Snowflake strongly preferred).
• BI Proficiency: Experience building and delivering enterprise dashboards in Tableau and/or Sigma, with an understanding of how data modeling decisions impact visualization and self-service analytics.
• Engineering Standards: Experience with code review processes, CI/CD pipelines, testing frameworks, and documentation practices.
• Governance Knowledge: Strong understanding of data governance principles, data integrity, and access control best practices.
• Stakeholder Management: Excellent interpersonal and communication skills with a proven ability to partner with business stakeholders and translate requirements into technical solutions.
• Leadership Potential: A collaborative mindset with the desire and aptitude to step into people management, mentor engineers, and build team culture.
• Self-Starter: Creative, proactive mindset with the ability to work independently and manage priorities across multiple workstreams.
• Education: Bachelor’s degree in Computer Science, Engineering, Data Analytics, Mathematics, or a related technical field (or equivalent professional experience).
• Prior experience in a technical lead or team lead capacity, even without formal management title.
• Experience supporting Product and/or Customer Success/Value business domains.
• Familiarity with data cataloging and metadata management tools (e.g., Atlan, Alation).
• Experience working in globally distributed teams with offshore/onshore collaboration models.
• Exposure to data quality frameworks and observability tooling.
• Track record of driving model deprecation, optimization, or cost-reduction initiatives in large dbt environments.