Senior AI Data Engineer for High-Throughput Pipelines

Morgan McKinley; Santo Niño 1st; On-site; PHP 800,000 - 1,400,000; Full time

Job summary

Morgan McKinley is seeking a Senior AI / Data Engineer to design, build, and optimize high-throughput data architectures for scalable analytics and AI/RAG applications. You will work with data scientists, analysts, and system owners to translate business needs into robust data pipelines.

You will develop batch and streaming pipelines using modern big data technologies, ensure data security, and govern metadata while collaborating across enterprise systems and APIs.

Qualifications

• Bachelor’s degree in a related technical field.
• 5 to 8+ years of hands-on experience in data engineering or large-scale big data applications.
• Strong proficiency in Python, PySpark, and Advanced SQL.
• Practical experience with Hadoop, Cloudera, Apache Spark, and workflow orchestration tools like Apache Airflow.
• Excellent verbal and written communication skills bridging technical solutions with business requirements.

Responsibilities

• Build and optimize batch and streaming data pipelines for high-volume datasets using modern big data technologies.
• Extract, transform, and organize complex network telemetry and business data across APIs, relational databases, and enterprise systems.
• Automate manual workflows, enforce strict data security standards, and manage enterprise metadata governance.
• Partner with data scientists, analysts, and system owners to support data visualization, AI/RAG solutions, and reporting platforms.

Skills

Python

PySpark

Advanced SQL

Hadoop

Cloudera

Apache Spark

Airflow

Education

Bachelor's degree in CS/Engineering

Job description

Morgan McKinley is seeking a Senior AI / Data Engineer to design, build, and optimize high-throughput data architectures for scalable analytics and AI/RAG applications. You will work with data scientists, analysts, and system owners to translate business needs into robust data pipelines.

You will develop batch and streaming pipelines using modern big data technologies, ensure data security, and govern metadata while collaborating across enterprise systems and APIs.