Data Engineering Jobs in Philippines
There are 1,081 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 269
- Lead 89
- Middle 28
- Junior 13
- Staff 13
- C-level 4
Who is hiring
- 1000+ employees 126
- 501-1000 employees 37
- 11-50 employees 8
- 51-200 employees 8
- 201-500 employees 1
Data Engineer
Builds Power BI dashboards and reports to turn raw sales data into clear, actionable insights for stakeholders.
Onsite AI-Driven Manufacturing Data Engineer
Builds and maintains AI-driven data tools to optimize manufacturing processes using SQL, Python, and Excel.
Data Engineer
Builds and automates ETL pipelines to feed reports, dashboards, and marketing analytics from raw data.
Data Engineer
Designs and maintains scalable data pipelines and databases for a real-estate brokerage, using Python, SQL, AWS, and ETL tools.
Data Engineer
Designs and maintains scalable data pipelines and ETL processes using SQL, Python, and cloud tools to support analytics and decision-making.
Databricks Data Engineer — Build Scalable Data Pipelines
Designs and maintains scalable data pipelines on Databricks, building ETL/ELT processes for large datasets using Python and SQL.
Data Engineer (AI Experienced)
Build and deploy AI systems for cost estimation and optimization, including LLM-powered applications and MLOps pipelines integrated with enterprise platforms.
Data Engineer: Lakehouse Pipelines for AI & Analytics
Design and scale cloud-native data pipelines and lakehouse infrastructure to power analytics, automation, and AI systems for a global data solutions firm.
Data Engineer
Leads data engineering for a bank’s analytics group, ensuring secure, high-quality data pipelines and tools to support modeling and visualization.
Senior Data Engineer
Senior Data Engineer builds and maintains Azure-based data pipelines and warehouses using Databricks, Azure Data Factory, SQL, and Python to power BI reports and global analytics.
Senior Data Engineer
Build and optimize data pipelines using Microsoft Fabric, SQL Server, and Dynamics 365 to integrate and transform large datasets, then deliver insights via Power BI dashboards for business stakeholders.
Senior Data Engineer
Build and scale a cloud-native data platform in Snowflake, owning ELT pipelines, data models, and governance to deliver trusted analytics and self-service capabilities for a fintech client.
Senior Data Engineer
Design and build scalable cloud data pipelines using Azure Data Factory, Snowflake, and Databricks to power analytics and reporting for enterprise clients.
Data Engineer
Build and maintain scalable data pipelines for market abuse surveillance, ensuring regulatory compliance by ingesting trade, market, and communications data into AWS-based systems.
AI-Driven Data Engineer for Operational Excellence
Senior data engineer building AI-driven analytics and automation tools to optimize operations for Marsh McLennan’s Asia Pacific teams.
Senior Snowflake Data Engineer
Build and optimize Snowflake data pipelines, ETL/ELT workflows, and GenAI integrations using Snowpark and Cortex AI features.
Senior Data Engineer (AWS & Snowflake)
Design and build cloud-native data pipelines and AI solutions using AWS and Snowflake, ensuring scalable, secure, and high-performance data infrastructure for analytics and AI initiatives.
Senior Data Engineer (Snowflake / Redshift)
Senior Data Engineer builds and optimizes cloud data platforms using Snowflake and Redshift to power analytics and reporting across a fintech organization.
AWS Data Engineer - ETL Pipelines & Real-Time Data
Build and maintain ETL pipelines using Python, PySpark, AWS Glue, Step Functions, and Lambda to process and transform data for reporting and analytics.