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Power BI Analytics Engineer: Data Modeling & Dashboards
Designs and builds Power BI data models, ETL pipelines, and dashboards to deliver analytics solutions for safeguards management.
Junior Data Analyst: Grow in Data Pipelines & Dashboards
Build and maintain data pipelines and dashboards to track business performance using SQL, Excel, and BI tools.
Senior Data Engineer: Python, SQL & AWS (Hybrid - Makati)
Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows using Python, SQL, PySpark, AWS, and Airflow in a hybrid Makati office.
Senior Data Engineer - ETL & AI-Powered Pipelines
Owns and scales ETL pipelines for healthcare data using PySpark, Python, SQL, and AWS, while ensuring PHI/PII security and governance in a regulated environment.
Senior Data Engineer (Python, SQL, ETL, AWS)
Designs and maintains scalable data pipelines using Python, PySpark, SQL, and AWS services like MWAA/Airflow for ETL/ELT workflows.
Informatica Data Engineer – ETL & Data Quality Expert
Designs and maintains enterprise ETL pipelines using Informatica PowerCenter and IICS, ensuring data quality and integration for scalable data workflows.
Sr. Specialist, Data Engineering
Designs and maintains scalable data pipelines and warehouses to feed analytics, BI, and AI/ML models using cloud platforms like AWS, Azure, or GCP.
Hybrid Data Engineer: Azure Pipelines & Architecture
Designs and maintains scalable ETL/ELT pipelines and cloud data architecture using Azure tools, ensuring data quality and compliance in a hybrid work setup.
Azure Data Engineer — Scalable ETL & Data Architecture
Designs and maintains scalable Azure-based ETL/ELT pipelines and data warehouses to support analytics and operations for a global insurance provider.
Data Engineer / Cloud Data Engineer (AI Center of Excellence)
Design and build enterprise-scale data platforms (lakes, lakehouses, ETL/ELT pipelines) that feed AI and analytics workloads, using cloud-native tools like Microsoft Fabric, Databricks, and Snowflake.
Data Engineer (IBM Cognos)
Build and maintain analytics and reporting solutions using IBM Cognos and Power BI, extracting and transforming data to deliver insights that drive retail banking decisions.
Lead Data Engineer
Lead Data Engineer responsible for designing, building, and maintaining scalable healthcare data pipelines in AWS, handling PHI/PII securely, and integrating AI/ML for mapping and data quality while owning the full pipeline lifecycle from development to production.
Full Stack Data Engineer (Python) - Hybrid setup
Builds and maintains scalable data pipelines and integrations using Python, handling ETL/ELT workflows, database interactions, and API connections to unify disparate data sources for business use.
Senior Data Engineer | Hybrid, Azure & Pipelines
Designs and maintains scalable ETL/ELT pipelines and cloud data architecture on Azure, ensuring data quality and compliance while collaborating with engineers and architects.
Data Engineer: Python & SQL for Scalable Pipelines
Designs and maintains scalable data pipelines and storage systems using Python and SQL, ensuring data quality through ETL and automated checks.
Microsoft Fabric Data Engineer
Build and scale an enterprise data lakehouse using Microsoft Fabric, designing data layers, pipelines, and models to power Power BI, AI/ML, and Copilot initiatives.
Data Engineer
Build and maintain scalable data pipelines on Snowflake using SnowPipe and dbt, ensuring clean, reliable data for analytics and AI/ML workloads.
Data Engineer Manager
Leads a team that designs, builds, and maintains automated data pipelines in a cloud-native environment, ensuring clean, governed data for analytics and downstream systems using tools like Spark, Airflow, Snowflake, and Databricks.
Informatica Data Engineer-Data Integration
Designs and maintains ETL pipelines using Informatica PowerCenter/IICS to integrate enterprise data from databases like Oracle and SQL Server into data warehouses.
Data Engineer (Python/SQL)
Builds and maintains scalable data pipelines, ETL processes, and data models using Python, SQL, and big data tools like Spark/Hadoop to ensure data quality and accessibility for business stakeholders.