Principal Data Engineer

Posted 9 days agoViewed

💎 Seniority level: Principal, 8+ years

📍 Location: United States, Canada, EST

💸 Salary: 150000.0 - 180000.0 USD per year

🔍 Industry: SaaS

🏢 Company: Ceros👥 101-250💰 $100,000,000 Private over 4 years agoAdvertising Content Creators Content Marketing Graphic Design Software

🗣️ Languages: English

⏳ Experience: 8+ years

🪄 Skills: AWSPythonSQLETLData engineeringCommunication SkillsAnalytical SkillsData visualizationStakeholder managementCRMData modelingSaaSA/B testing

Requirements:

8+ years of experience in data engineering, product analytics, or SaaS.
Strong experience with SQL, AWS Redshift, and ETL pipelines.
Proficiency with BI tools (Looker, Metabase, Mixpanel).
Experience with AI-driven analytics and NLP techniques.
Strong communication and stakeholder management skills.
Highly organized and capable of managing multiple priorities.
Experience in SaaS, especially in content creation or enterprise tech.
Familiarity with customer feedback and conversational intelligence tools.
Hands-on experience with Python or scripting languages for data automation.

Responsibilities:

Own and optimize data architecture, ensuring scalability and efficiency.
Partner with Ops Engineering to improve data pipelines and integrations.
Manage and optimize AWS Redshift and other key platforms.
Define and enforce data governance best practices.
Extract insights from customer interactions using AI-driven analytics.
Identify trends in feature requests, pain points, and product issues.
Develop dashboards to provide actionable insights for stakeholders.
Ensure data is structured and available for sales tracking, forecasting, and segmentation.
Support revenue modeling and churn risk analysis.
Maintain CRM data integrity and enable data-driven sales strategies.
Support A/B testing and controlled experiments to optimize product and sales decisions.
Develop models to measure customer engagement and sales effectiveness.
Build predictive models for customer retention and revenue growth.
Work with stakeholders to enable data-driven decision-making.
Develop self-service tools and training materials.
Promote best practices and data accessibility across teams.

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