Senior Data Engineer: AI/ML & GenAI Data Pipelines

Eclaro; Taguig; On-site; PHP 800,000 - 1,100,000; Full time

Job summary

Eclaro is seeking an experienced Data Engineer with AI/ML expertise to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong hands-on experience in cloud-based data engineering, data integration, data modeling, and AI-ready data architecture.

Responsibilities include building batch and real-time pipelines, enabling AI/ML use cases, collaborating with analysts and BI teams, implementing governance, and supporting MLOps.

Qualifications

• 5+ years of Data Engineering experience
• Experience with Snowflake, Python, SQL, Spark, ETL/ELT development
• Experience in AI data architecture and Generative AI solution development, including building AI agents and data pipelines that support AI workloads

Responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines.
• Enable AI/ML and Generative AI use cases by creating high-quality, reliable datasets.
• Collaborate with Data Analysts, AI Engineers, BI teams, and business stakeholders to support model development and deployment.
• Implement data quality, monitoring, security, and governance best practices.
• Support MLOps and AI workflows, including feature engineering and data preparation.
• Optimize data processing performance, scalability, and cost efficiency.

Skills

Data Engineering

AI data architecture

Generative AI solution development

Tools

Snowflake

Python

SQL

Spark

ETL/ELT development

Job description

Eclaro is seeking an experienced Data Engineer with AI/ML expertise to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong hands-on experience in cloud-based data engineering, data integration, data modeling, and AI-ready data architecture.

Responsibilities include building batch and real-time pipelines, enabling AI/ML use cases, collaborating with analysts and BI teams, implementing governance, and supporting MLOps.