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
Japanese Big Data Engineer (SQL, Python) Php 100,000 - Php 200,000 a month
Big Data Engineer builds and maintains scalable data systems using SQL and Python to design analytics applications and integrate Big Data tools for a global IT/BPO firm.
Senior Data Platform Engineer
Designs and builds scalable data pipelines and cloud-based data platforms using Azure, Databricks, and Python/TypeScript to enable analytics and data-driven decisions.
Data Platform Engineer -MRF-00661
Builds and maintains enterprise data platforms, automating security, metadata, and lifecycle management with Python and SQL to ensure data integrity and accessibility.
Data Quality Engineer - Hybrid Role & Data Governance
Ensures data accuracy by designing tests, monitoring quality, and reporting issues using SQL and Python in a hybrid role.
Data Platform Engineer - hybrid BGC
Build and maintain enterprise data platforms, focusing on security, metadata management, data quality, and lifecycle automation using SQL and Python.
Cloud Data Platform Engineer
Designs, builds, and optimizes cloud data platforms on AWS, Azure, and GCP to support AI-assisted decision-making and scalable data products.
AWS Data Platform Engineer - Japanese Bilingual
Builds and maintains AWS-based data pipelines and warehouses using EMR, Glue, Kinesis, RedShift, and DynamoDB, plus open-source tools like Airflow and dbt.
Data Platform Engineer: Governance, Security & Automation
Implement and manage enterprise data platforms, focusing on governance, security, and automation using Python and SQL.
Security Engineer - Data Platform
A security engineer focused on hardening data platforms by deploying and maintaining security tools (proxies, IDS, scanners) while enforcing encryption, authentication, and compliance in both on-prem and cloud environments for a global payments company.
Data Platform Operations Engineer
Maintains and optimizes enterprise data platforms (MSSQL, Microsoft Fabric) and data pipelines, ensuring reliability and performance while supporting migrations to modern cloud solutions.
Real-Time Market Data Engineer – Low Latency
Build and maintain low-latency market data platforms for trading systems, ensuring data accuracy and availability in Linux and cloud environments.
Remote Senior Data Engineer: AWS & Confluent Real-Time Data
Designs and builds scalable real-time data pipelines using AWS and Confluent for a staffing solutions provider.
Data Platform Engineer
Build and maintain scalable data pipelines and cloud data platforms using Azure Databricks, Data Factory, and IaC tools like Terraform to deliver reliable analytics infrastructure.
Data Platform Engineer
Builds and optimizes Snowflake data warehouses and ETL/ELT pipelines using dbt and Airflow, collaborating with analysts to deliver clean, scalable data models.
Data Engineer (6-Month Hybrid) - AWS & Databricks Pipelines
Design and maintain AWS and Databricks data pipelines to support global supply-chain analytics in a hybrid role.
Senior Data Engineer (GCP) I WFH - Up to 110K Salary
Designs and optimizes cloud-based data warehouses (GCP/BigQuery) for healthcare analytics, building pipelines and models to support Clinical, Patient Accounting, and Corporate teams while ensuring data quality and performance.
Lead Data Engineer - Azure Databricks, Spark TB-scale ETL
Design and maintain TB-scale ETL pipelines on Azure Databricks and Spark, ensuring data quality and governance while collaborating with cross-functional teams.