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: Pipelines & Analytics
Designs, builds, and maintains data pipelines and analytics infrastructure using SQL and visualization tools in a hybrid Manila office.
Data Engineer
Build and maintain scalable batch and streaming data pipelines in AWS + Databricks, using Python, SQL, and modern lakehouse architectures to power analytics and reporting for a fast-growing fintech lender.
Analytics Data Engineering
Designs and maintains data infrastructure and pipelines using Apache Kafka, Spark, and Airflow to support AI/ML and BI workloads.
Data Engineer, AI Pipelines & Lakehouse (Hybrid)
Builds and maintains data pipelines for AI training and analytics using Databricks, GCP, and Azure, ensuring clean data for models and reporting.
Data Engineer
Build and maintain scalable data pipelines using Databricks, GCP, and Azure to power AI model training, RAG-based search, and enterprise analytics.
Hybrid Data Engineer: Data Warehousing & Pipelines
Builds and maintains data warehouses and ETL pipelines using Python, SQL, and Azure Data Factory to support healthcare analytics and reporting.
Senior Data Engineer: AI-Driven Data Pipelines
Build and maintain AI-driven data pipelines using SQL, Python, and cloud services like AWS to ensure high-quality data for analytics and machine-learning applications.
Senior Data Engineer - AI-Ready Data Pipelines
Design and maintain scalable data pipelines for a fintech platform, enabling analytics and AI use cases across warehouses, lakes, and lakehouse architectures.
Data Engineer: Scale Data Pipelines for AI & BI
Designs, builds, and deploys data pipelines to power AI/ML models and BI insights for customers using cloud platforms and big-data tools.
Data Engineer: Build AI-Ready Data Pipelines
Design and deploy scalable data pipelines for AI/ML and BI using Spark, Hadoop, Kafka, and SQL warehouses while ensuring data quality and governance.
Data Engineer: AI Data Pipelines & Lakehouse (Hybrid)
Build and maintain data pipelines for AI model training and analytics using Databricks, GCP, and Azure, ensuring clean, reliable data and supporting BI dashboards.
Senior Data Engineer: Scale Data Pipelines & AI
Design and scale production-grade data pipelines and cloud-native infrastructure to power analytics, automation, and AI systems for a global enterprise.
Senior Data Engineer
Design and maintain scalable data pipelines and integrations for education technology products, ensuring data quality, governance, and security while mentoring teams.
Operational Excellence & AI Data Engineer
Build and deploy AI-driven analytics, automation, and data solutions to streamline reinsurance operations and improve decision-making across Asia Pacific.
Data Engineer
Designs and builds cloud-based data pipelines and warehouses in GCP/BigQuery to support healthcare analytics, ensuring data integrity and performance for clinical and corporate insights.
Senior Data Engineer: Cloud Data Pipelines & Warehousing
Design and build scalable cloud data pipelines and warehouse models using Snowflake, PostgreSQL, and AWS tools to deliver reliable data assets for BI and analytics.
AI Engineer (LLM & Data Engineering)
Build and deploy AI models (LLMs, ML) and data pipelines for healthcare insights, recruiter automation, and personalized digital experiences using Python, PyTorch/TensorFlow, and LangChain.
Data Engineer
Build and optimize data pipelines and storage systems using Spark, Hadoop, Snowflake, and Airflow to process large-scale datasets for analytics and modeling.
Data Engineer
Build and maintain scalable data pipelines and warehouses using BigQuery, ClickHouse, Airflow, Kafka, and CDC tools to power analytics and reporting.