Hybrid Data Engineering Consultant — AI & Data

Internetwork Expert; Taguig; On-site; PHP 900,000 - 1,500,000; Full time

Benefits offered by this job

Hybrid setup

Professional development budget

Health benefits

Performance reviews

Job summary

Thinking Machines is hiring an Engineering Consultant (Data Engineering) to collect, secure, transform, and store data for data science workflows. You will architect analytics platforms, build ETL pipelines, and drive data-driven decisions for diverse clients.

The role emphasizes security, mentorship, and consultant-facing work, with a fast-paced environment and opportunities for growth.

Qualifications

• 3+ years of work experience in a data engineering or software engineering role.
• Proficiency in Python programming language, SQL, and Airflow — PostgreSQL and analytics tooling familiarity.
• Experience managing various cloud environments (AWS, GCP; Azure a bonus).
• Experience with Google/Azure stacks and tools like BigQuery, Dataflow, TensorFlow, Databricks.
• Security-conscious mindset handling client data with established guidelines.
• Ability to make or build things fast and mentor others.
• Demonstrated mentorship and/or project leadership experience.
• Strong communication skills for client and internal collaboration.
• Consultative mindset and a generalist point of view with initiative.

Responsibilities

• Architect analytics platforms for SaaS companies and NGOs; build data collection and warehousing systems.
• Develop and optimize ETL pipelines and data transformations.
• Collaborate with clients and internal teams; document technical work and provide guidance.
• Mentor junior engineers and contribute to team growth and learning.

Skills

Python

SQL

Airflow

Security-conscious mindset

Mentorship

Communication

Consultative mindset

Generalist perspective

Initiative

Tools

dbt

BigQuery

Snowflake

PostgreSQL

AWS

GCP

Azure

TensorFlow

Dataflow

Azure Data Factory

Databricks

Job description

Thinking Machines is hiring an Engineering Consultant (Data Engineering) to collect, secure, transform, and store data for data science workflows. You will architect analytics platforms, build ETL pipelines, and drive data-driven decisions for diverse clients.

The role emphasizes security, mentorship, and consultant-facing work, with a fast-paced environment and opportunities for growth.