Data Engineering Jobs in Philippines
There are 1,079 open Data Engineering jobs in Philippines on freehire right now. 303 of them were posted recently. The skills employers ask for most often are sql, data-pipelines and analytics.
Most requested skills
- sql 58%
- data-pipelines 52%
- analytics 49%
- python 49%
- cloud 47%
- etl 46%
- data-engineering 43%
- data-quality 36%
How the work is done
- Hybrid 121 · 11%
- Remote 55 · 5%
- Onsite 15 · 1%
Visa sponsorship offered in 25% of the 16 postings that state a position on it.
Seniority
- Senior 268
- Lead 87
- Middle 28
- Junior 13
- Staff 13
- C-level 4
Who is hiring
- 1000+ employees 124
- 501-1000 employees 37
- 11-50 employees 8
- 51-200 employees 8
- 201-500 employees 1
Data Engineering Lead - Asset Management
Lead a team to design and build data pipelines and transformations using Azure and Databricks, turning raw data into insights for asset management.
Data Engineer, Managed Services
Build and maintain Azure-based data pipelines and Power BI reports for clients, troubleshooting issues and mentoring junior engineers using Microsoft’s data stack.
Middle Data Engineer
Build and optimize data pipelines, write clean code, and collaborate with teams to deliver reliable data solutions using batch, streaming, or hybrid approaches.
Azure Data Engineer: Pipelines, Databricks & Dashboards
Builds and maintains Azure-based data pipelines, integrates Databricks for analytics, and creates Power BI/Tableau dashboards to support business insights.
Senior Data Engineer - Scalable Data Pipelines (C#, SQL)
Senior Data Engineer builds and maintains scalable data pipelines in C# and SQL for Amadeus Hospitality, focusing on ETL, BI, and cloud-based data solutions.
Senior Data Engineer
Build and maintain scalable data pipelines and cloud data warehouses using Azure Data Factory, Snowflake, dbt, SQL, and Python to power marketing analytics and enterprise reporting.
Data Engineer
Builds and maintains scalable ETL pipelines on Databricks and AWS to turn raw data into clean, analytics-ready datasets for reporting and business insights.
Data Scientist/Data Engineer (Python, AI, RAG, LangChain)
Build and improve AI developer tools using Python, RAG, and LangChain to enhance engineering velocity and integrate AI workflows.
Lead Azure Data Engineer & Multicloud Data Architect
Lead a team to design and build scalable data pipelines using Azure Databricks, ADF, and PySpark, while integrating with AWS, Snowflake, and BigQuery in hybrid/multi-cloud environments.
Data Engineer
Builds and maintains data pipelines, ETL scripts, and APIs in Python and AWS to clean, process, and warehouse enterprise data for analytics and reporting.
Data Engineer Lead
Lead the end-to-end data architecture—ingestion, processing, modeling, and consumption—using Python, PySpark, Airflow, and AWS services to enable reliable reporting and LLM-driven analytics at scale.
Senior Data Engineer: Data Pipelines, Cloud & Governance
Senior Data Engineer builds and governs cloud-based data pipelines and models for edtech products, ensuring scalable, reliable data infrastructure.
Retail Analytics Data Engineer
Builds and maintains ELT/ETL pipelines to transform retail transactional data into governed datasets for analytics, reporting, and forecasting.
Azure Data Engineer — Scalable Pipelines & Data Architecture
Designs and maintains scalable Azure data pipelines and architectures, collaborating with scientists and analysts to ensure quality, security, and compliance using Azure Data Factory and Databricks.
Data Engineer - Night Shift
Builds and maintains enterprise data pipelines and analytics platforms using SQL, ETL/ELT, and cloud tools like Microsoft Fabric to support reporting and AI initiatives.
Data Engineer (4x Onsite, QC)
Build and maintain data pipelines for a retail company focused on health and wellness, processing large datasets to support business decisions using Python, SQL, and cloud platforms like AWS and Databricks.
Microsoft Fabric Data Engineer (For Pooling)
Designs and maintains Microsoft Fabric data pipelines, OneLake environments, and analytics-ready data using Azure services, PySpark, and T-SQL.