Top Data Engineer Jobs in Davao City

Develops, maintains, and optimizes SQL Server databases supporting enterprise applications. Responsibilities include writing complex T-SQL queries and procedures, profiling data, improving data quality and performance, documenting schemas and data flows, supporting ETL processes, and ensuring secure coding and HIPAA compliance. The role collaborates with cross-functional teams to deliver data milestones and application improvements. This is a work-from-home position supporting US hours and night-shift schedules.

Execute structured and exploratory QA tests for gameplay data-collection software, install and maintain software on personal hardware, reproduce and document bugs, analyze logs, and escalate issues. Validate PC hardware, GPU performance, drivers, and redundant network connectivity to ensure reliable data-collection sessions. Communicate concise technical findings in written English through Slack and triage feedback for client engineering teams.

Build and optimize ETL/ELT pipelines feeding BigQuery, audit and troubleshoot data quality, and create reliable Looker Studio dashboards. The role supports sales leaders by turning raw data into accurate, actionable insights, improving reporting performance, eliminating manual processes, and ensuring data integrity across Curvion’s revenue operations ecosystem.

Develop robotics datasets and evaluations for embodied AI systems. Responsibilities include defining data schemas, annotations, quality standards, collection protocols, validation tools, and review workflows. The role also involves running experiments to assess how data quality and structure affect model performance, collaborating with research, engineering, vendors, and customers, and taking research tools from conception through deployment.

Design, build, and maintain scalable data ingestion, transformation, modeling, warehousing, and ETL/ELT pipelines from diverse high-volume sources. Ensure data accuracy, security, validation, and efficient delivery for analytics and reporting. Improve infrastructure and automate processes while collaborating with stakeholders, documenting solutions, supporting team members, and modeling datasets for BI tools such as Power BI, Tableau, and Apache Superset.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design, build, and maintain scalable ETL/ELT pipelines and data architecture; integrate multiple data sources; ensure data quality, governance, security, and performance; monitor pipelines; support BI, analytics, and ML; document models and workflows; collaborate with stakeholders.

Lead HUD's data quality strategy for RL training data: build QC systems, validate synthetic data at scale, design evaluation experiments, partner with researchers and vendors, convert research insights into production validation pipelines and tools, and mentor research engineers.

Monitor daily data intake across channels, perform QA to detect inconsistencies or unusual trends, troubleshoot ingestion issues, document findings, and propose process/product improvements while working scheduled shifts.

Hands-on senior data engineer role building and operating client-specific ELT pipelines and three-layer dbt projects on cloud warehouses (pref. BigQuery). Own pipeline operations, reconciliation and testing, semantic layer/metric definitions (Cube.dev), freshness/anomaly monitoring, PII-aware quality frameworks, and translate client domain discovery into reliable business marts to power dashboards and AI queries.