Senior Data Engineer

Company Description

Dream Opportunity is a global organization focused on expanding access to high-income career pathways for under-resourced students.

We partner with multi-billion-dollar companies including JPMorgan Chase, AT&T, EY, Blackstone, Paramount, Informa, Kelloggs, Kellanova, and others to provide students with real exposure to careers and professional networks.

Building on this foundation, we are launching Dreamari, a global AI-powered, gamified ed-tech platform designed to help students discover careers, build skills, and unlock opportunity at scale.

Dreamari will launch with immediate distribution across eight countries: the United States, the United Kingdom, Canada, India, the Philippines, Mexico, Singapore, and the UAE.

We are forming the first selected core technical team to build this platform from the ground up. These roles will influence product architecture, global scalability, and long-term technical direction.

Role Overview

As a Senior Data Engineer, you will design and build the data architecture that powers the platform.

You will own data pipelines, warehousing strategy, and distributed systems that process user behavior across multiple countries.

This is a founding engineering role with direct influence on system reliability, performance, and long-term scalability.

We are looking for engineers who have built production-grade data systems at scale.

What Youll Do

• Design and implement scalable data pipelines processing high-volume user activity
• Build and maintain data warehouses and storage architecture
• Develop reliable ETL / ELT (Extract, Transform, Load) workflows across distributed systems
• Optimize data systems for performance, cost efficiency, and reliability
• Support real-time and batch data processing needs
• Partner closely with ML engineers to ensure clean, well-structured training data
• Maintain high standards of documentation, monitoring, and operational discipline
• Contribute to long-term data architecture decisions

Required Skills & Experience

• 5+ years of professional experience in data engineering or big data systems
• Strong proficiency in Python and SQL
• Experience building distributed data systems in production
• Hands-on experience with modern data stack tools (e.g., Snowflake, Databricks, or equivalent)
• Experience designing and maintaining scalable data warehouses
• Experience building high-performance data pipelines
• Strong architectural thinking and systems-level problem solving
• Strong communication skills and ability to collaborate in a fast-moving startup environment

Nice to Have

• Experience supporting machine learning pipelines
• Experience working with event-driven architectures
• Exposure to real-time streaming systems

Compensation & Benefits

Compensation: 4850 LPA (approximately $54,000 USD annually)

Equity: Meaningful equity participation as an early founding engineer

Role Type: Full-time, founding technical role

Ownership: High autonomy and real influence over data architecture decisions

Growth: Opportunity to build global-scale data infrastructure from day one