Data Engineer - MANILA (CONTRACT)

Artefact; Manila; On-site; PHP 600,000 - 1,100,000; Full time

Job summary

Artefact is a forward‑looking data consulting firm helping clients turn data into business value. We seek a Data Engineer to design, build, and maintain scalable data solutions using Python, SQL, and cloud platforms.

You will work with Snowflake, Databricks, and GCP, delivering end‑to‑end data pipelines and ML‑friendly workflows. You will collaborate with data scientists and business stakeholders, contributing to data governance, warehousing, and real‑time processing efforts in a fast‑paced,

Qualifications

• 2–5 years of experience as a Data Engineer or similar
• Strong proficiency in Python and SQL
• Hands-on experience with Google Cloud Platform (GCP) and its data ecosystem
• Experience with Snowflake and/or Databricks for data engineering and analytics
• Experience designing and implementing ETL/ELT pipelines for large datasets
• Familiarity with Azure or AWS is a plus
• Experience with Spark and Kafka is highly valued
• Understanding ML workflows and integration into pipelines is an advantage
• Proven problem-solving and client-facing collaboration skills
• Minimum Bachelor's degree in CS, ECE Eng, or other technical discipline

Responsibilities

• Data Pipeline Development: Build, maintain, and optimise scalable data pipelines.
• Database & Data Warehouse Management: Manage databases and data warehouses for integrity and performance.
• Cloud Data Engineering: Design and deploy scalable data solutions on cloud platforms (GCP focus).
• Snowflake & Databricks: Work with Snowflake and Databricks for processing and analytics.
• ETL/ELT Development: Design and implement ingestion and transformation processes.
• Machine Learning Integration: Collaborate to put ML models into production pipelines.
• Big Data & Streaming: Use Spark/Kafka for large-scale real-time processing where applicable.
• Client & Stakeholder Collaboration: Translate requirements into scalable data solutions.

Skills

Python

SQL

GCP

Snowflake

Databricks

ETL/ELT

Spark

Kafka

Data pipelines

Data warehousing

Education

Bachelor's degree in Computer Science, Electrical & Communication Eng or Engineering

Tools

Snowflake

Databricks

GCP

Job description

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. We are dedicated to transforming data into business impact across the entire value chain of organisations—and we’re proud to say we’re enjoying skyrocketing growth.

At the backbone of our consulting missions, our Data Consulting team brings together more than 400 consultants covering a wide range of areas, including data engineering, data science, data marketing, data governance, strategy consulting, product ownership, and more.

What you will be doing

As a Data Engineer, you will design, build, and maintain robust and scalable data solutions, using technologies such as Python, SQL, GCP, Snowflake, and Databricks to enable efficient data processing and analytics.

Your responsibilities will include:

• Data Pipeline Development: Build, maintain, and optimise scalable data pipelines to facilitate seamless data flow across systems and platforms.


• Database & Data Warehouse Management: Manage databases and data warehouses, ensuring data integrity, performance, and efficient storage and retrieval.


• Cloud Data Engineering: Design and deploy scalable data solutions on cloud platforms, with a strong focus on Google Cloud Platform (GCP). Exposure to Azure and AWS is also valuable.


• Snowflake & Databricks: Work with modern data platforms such as Snowflake and Databricks to build and optimise data processing, transformation, and analytics solutions.


• ETL/ELT Development: Design and implement ETL/ELT processes to ingest, transform, and integrate data from multiple sources.


• Machine Learning Integration: Collaborate with Data Science and Machine Learning teams to integrate models into production data pipelines and workflows.


• Big Data & Streaming: Work with technologies such as Spark and Kafka for large‑scale and real‑time data processing where applicable.


• Client & Stakeholder Collaboration: Work closely with business and technical stakeholders to understand requirements and translate them into scalable data solutions.

What we are looking for

• 2–5 years of experience as a Data Engineer or in a similar data‑focused engineering role.


• Strong proficiency in Python and SQL, with hands‑on experience in database management and data pipeline development.


• Hands‑on experience with Google Cloud Platform (GCP) and its data ecosystem.


• Experience with Snowflake and/or Databricks for data engineering, data warehousing, transformation, or analytics workloads.


• Experience designing and implementing ETL/ELT pipelines and working with large‑scale datasets.


• Familiarity with other cloud platforms such as Azure or AWS would be an advantage.


• Experience with technologies such as Spark and Kafka is highly valued.


• Understanding of Machine Learning workflows and experience supporting ML model integration would be an advantage.


• Proven problem‑solving skills and a solution‑oriented mindset.


• Experience working directly with business stakeholders or clients, either internally or externally.


• Excellent communication skills and the ability to collaborate effectively across technical and non‑technical teams.


• Strong business acumen and an interest in client‑facing and business‑facing roles.


• Adaptability, curiosity, and a start‑up mentality to thrive in a fast‑paced and dynamic environment.


• Minimum Bachelor's degree in Computer Science, Electronics & Communication Engineering, Engineering, or another relevant technical discipline.

Artefact is the place to be: come and build the future of Data & AI

Innovation: We have a passion for creating impactful projects and believe innovation can come from anyone.

Action: We make things rather than telling people how to make them.

Collaboration: We believe in bringing talented people together, winning together, and learning from each other.