About the job
Join CloudFactory, a mission-driven organization dedicated to harnessing the power of AI for global transformation. We merge cutting-edge technology with a diverse, skilled workforce to convert unmanageable data into actionable insights, creating a significant impact worldwide.
Beyond being a job, we are a global family built on trust and the conviction that purposeful work changes lives. Our focus on earning, learning, and service shapes our mission to connect one million individuals to fulfilling careers and cultivate inspirational leaders.
Our Culture
At CloudFactory, we strive to foster an environment where every individual feels empowered, valued, and inspired to express their true selves. Our core values include:
- Mission-Driven: Committed to generating economic and social benefits.
- People-Centric: Deeply invested in our team's growth, wellness, and inclusivity.
- Innovative: Embracing change and collaboratively seeking better solutions.
- Globally Connected: Encouraging collaboration among diverse cultures and perspectives.
If you are excited about innovation, collaboration, and making a meaningful impact, we invite you to apply!
Role Summary
As a Senior Analytics Engineer, you will be responsible for the architecture, quality, and scalability of CloudFactory’s analytics infrastructure. You will guide a team in transforming raw data into clean, well-structured, and efficient data models that facilitate reliable, data-driven decision-making throughout the organization.
This role combines analytics engineering, data science, and technical leadership. You will advocate for top-notch engineering practices (version control, testing, CI/CD), create ML-ready data products, and collaborate closely with Data Engineering, Product, and Technology teams to deliver impactful insights.
Key Responsibilities
Analytics Engineering & Data Architecture
- Design, construct, and maintain scalable analytics data models utilizing DBT and Snowflake.
- Implement best practices in dimensional modeling (Kimball/Star Schema) and create ML-ready feature tables.
- Choose and execute suitable data storage and modeling strategies based on performance and scalability demands.
- Ensure high data quality, reliability, and thorough documentation across the analytics layer.
Advanced Analytics & Predictive Data Products
- Lead the development of predictive data products to assess user performance, churn risk, and customer health.
- Integrate fraud analytics and anomaly detection into core data transformations for proactive risk management.
- Utilize appropriate statistical and machine learning techniques, independently evaluating models and interpreting results.
