Marketing Analytics Engineer

OUR MISSION

At Redwood, we empower our customers with lights-out automation for their mission-critical business processes.

ABOUT US

Redwood Software is the leading orchestration platform for the autonomous enterprise, driving business transformation at the lowest total cost of ownership. Redwood empowers organizations to intelligently automate and orchestrate mission-critical business and IT processes across complex ERP, hybrid cloud, data and emerging agentic AI systems. Through its SaaS-first automation fabric—with AI embedded across the automation lifecycle—Redwood accelerates the path to autonomous operations. Backed by 30 years of experience and trusted by more than 50% of the Fortune 50, Redwood helps organizations unlock human potential to focus on innovation, growth and what’s next. 

CORE VALUES

One Team. One Redwood

Make Your Own Weather

Obsess over Customer Success

Work the Problem

Be Curious

Own the Outcome

Respect Each Other

YOUR IMPACT

We’re looking for a Marketing Analytics Engineer who will build, manage, and optimize the data and reporting infrastructure that powers marketing analytics. This role is responsible for developing scalable dashboards, ensuring data quality, and enabling self-service analytics across the organization.

You’ll work closely with marketing, RevOps, and analytics stakeholders to deliver reliable, automated, and high-quality reporting solutions. You will also play a key role in advancing our analytics capabilities through automation, data modeling, and AI-driven insights.

Dashboarding & Reporting Development

• Design, build, and maintain dashboards that track campaign performance, pipeline health, and funnel conversion
• Ensure dashboards are intuitive, performant, and aligned with stakeholder requirements
• Continuously optimize reporting for usability, scalability, and performance
• Translate defined business and analytics requirements into effective data visualizations and reporting structures

Data Modeling & Transformation

• Develop and maintain data models that support marketing analytics and reporting
• Transform and prepare data from multiple sources (CRM, marketing automation, product data) for analysis
• Ensure consistent definitions and logic across reporting layers
• Work with large datasets to enable accurate and scalable reporting

Data Quality & Integrity

• Own data validation processes to ensure accuracy, completeness, and consistency of marketing data
• Identify and resolve data discrepancies and inconsistencies across systems
• Partner with RevOps and data engineering teams to maintain reliable marketing data pipelines

Automation & Self-Service Analytics

• Automate recurring reporting and data workflows to reduce manual effort
• Enable self-service analytics by building scalable datasets and user-friendly reporting layers
• Develop alerting and monitoring systems to surface performance changes and anomalies
• Support stakeholders in accessing and querying data independently

AI & Advanced Analytics Enablement

• Implement AI-driven solutions for anomaly detection, trend identification, and insight generation
• Support predictive analytics and advanced reporting capabilities where appropriate
• Evaluate and integrate tools that improve analytics efficiency and scalability

Attribution & Advanced Modeling (Preferred)

• Develop and maintain attribution models across the marketing funnel
• Support customer journey analysis and channel impact measurement
• Continuously refine models based on business needs and data availability

YOUR EXPERIENCE

• 4–7 years of experience in business intelligence, analytics engineering, or a related field
• Expert SQL proficiency and experience working with large datasets
• Experience building complex dashboards using tools such as Tableau, Power BI, Looker, or Qlik
• Experience working with marketing and CRM data (e.g., Salesforce, Marketo, Google Analytics)
• Strong understanding of data modeling and data transformation techniques
• Experience building scalable and automated reporting solutions
• Strong attention to detail and problem-solving skills
• Familiarity with modern data stack tools (e.g., dbt, Snowflake, BigQuery, etc.)

Preferred

• Experience with Python or similar languages for data processing or automation
• Experience with AI/ML tools or workflows in analytics
• Experience with attribution modeling and customer journey analytics