Data Engineer

About the job

Steradium is a technology company focused on turning advanced artificial intelligence into practical solutions for businesses. Our team members collaborate in a modern, fast-paced environment that values curiosity, problem-solving, and continuous learning. We're currently building an AI-native engineering team from the ground up.

What you'll do

• The Data Engineer will design, build, and maintain scalable data pipelines that support analytics, AI models, and business intelligence initiatives.
• Daily responsibilities include developing and optimizing ETL processes, implementing data models, and managing data warehouses to ensure reliable, high-quality data.
• The role involves collaborating with stakeholders to understand data needs, define technical requirements, and deliver robust solutions.
• The Data Engineer will also monitor data workflows, troubleshoot issues, improve performance, and contribute to best practices in data engineering and governance.

What we're looking for

• Strong data engineering skills, including experience with building and maintaining production data pipelines.
• Proficiency in data modeling and designing structured and scalable data architectures.
• Hands-on experience with Extract Load Transform (ELT) processes and tools for ingesting and transforming data.
• Knowledge of data warehousing concepts and platforms used for storing and organizing analytical data.
• Ability to work with data analytics teams to deliver datasets that enable reporting, dashboards, and AI/ML use cases.
• Proficiency in one or more programming languages commonly used in data engineering (e.g., Python, Java, or Scala).
• Experience with cloud data platforms and services (e.g., AWS, Azure, or GCP) is highly beneficial.
• Familiarity with SQL and relational databases; exposure to NoSQL or big data technologies is a plus.
• Strong problem-solving skills, attention to detail, and ability to work independently in a remote environment.

How we work with AI

• Everyone has access to Google Gemini, Claude Code, and Codex in their daily loop. We measure output in shipped, reviewed, production-grade work, not in hand-typed lines.
• Everyone can use AI assistants for scaffolding, refactors, test generation, and exploring unfamiliar codebases, but people own every line that ships with their name on it.
• We expect everyone to know and understand where AI is unreliable: subtle concurrency, security boundaries, domain logic, anything where being confidently wrong is expensive.

What we offer

• Competitive salary package and 13th month pay
• Government-mandated benefits (SSS, PhilHealth, Pag-IBIG)
• Flexible working arrangements
• Annual learning budget plus company-provided AI tooling
• Mentorship program
• No graveyard shift, no mandatory overtime