Top Data Engineer Jobs in Caloocan

The Data Engineer will analyze raw data, build data systems, enhance data quality, develop tools, and meet business objectives.

The Data Engineer will analyze raw data, build data systems, enhance data quality, evaluate business needs, and develop analytical tools.

The Data Engineer will analyze and organize raw data, build data systems and pipelines, and improve data quality for business needs.

The Data Engineer will analyze raw data, build data pipelines, evaluate business needs, enhance data quality, and develop analytical tools.

The Data Engineer will analyze and organize raw data, build systems and pipelines, and develop analytical tools to enhance data quality.

Design, build, and maintain scalable data pipelines and ETL processes using Python and SQL. Optimize schemas and queries, deploy/manage data workloads on AWS, and collaborate with analysts and business teams to ensure data accuracy, availability, and governance.

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.

Support pre- and post-deployment data pipeline and product integration activities. Assist clients with data ingestion and configurations, monitor and maintain pipelines (e.g., Matillion), troubleshoot scripts and integration issues (PHP, Postgres), document procedures, and escalate complex problems to senior engineers while collaborating with support and product teams.

The role involves building and maintaining data pipelines, developing ETL components, testing, CI/CD deployment, and collaborating with the BA and Scrum Master on projects.

Design, develop, and maintain data pipelines and workflows (batch/streaming), ensure data quality and governance, write clean tested code, troubleshoot processing issues, collaborate in agile teams, produce documentation, and support deployments while growing technical skills under senior guidance.

Design, build, and maintain scalable data pipelines and storage on cloud platforms. Implement ETL, data models, data quality monitoring, governance, and collaborate with data scientists for analytics and reporting.

The Data Architect will design and implement data infrastructure, collaborating with teams to enhance data usage for analytics, automation, and AI, while ensuring compliance and governance.

The Senior Data Engineer will design and build data infrastructure and pipelines, enhance AI capabilities, and collaborate with teams on data solutions while mentoring junior engineers.

Support design, develop, test and deploy ETL/ELT pipelines for Finance data lake and warehouse. Provide L1/L2 platform support, implement data quality, validation and governance, maintain metadata/lineage, and collaborate with business users and analysts to translate requirements and enable BI self-service.

The Data Developer will design, expand, and optimize data pipelines, process data from various sources, and assist with data-related issues.

Designs, develops, and maintains Power BI dashboards, semantic/data models, and reporting datasets. Uses SQL and DAX to transform and validate enterprise data, partners with stakeholders to define KPIs, troubleshoots BI solutions, and contributes to governance and continuous improvement across GBS finance and operations.

The Data Engineer will develop and operate a cloud-based Manufacturing Data Lake, manage data pipelines, optimize solutions, and ensure efficient platform use for users.

Design, build and optimize complex Azure-based data pipelines and ETL solutions using Informatica and big-data technologies. Analyze sources, resolve data quality issues, implement automation, tune performance, and mentor junior team members to deliver end-to-end BI and real-time analytics solutions.

Design and maintain secure data platforms, optimize data workflows and processes, and collaborate with stakeholders to implement data solutions.

Build and operate AWS serverless infrastructure and data pipelines, design integrations across accounting and business apps, develop and test LLM-based financial agents, lead client discovery sessions, and document and standardize platform and agent implementations to maintain security and compliance.

Design, build, deploy, and maintain data processing applications and infrastructure; perform ETL, monitor production, resolve incidents, support stakeholders, and create proofs-of-concept and documentation.

Design, code, and maintain SQL procedures; troubleshoot database issues; review SQL code; create SSIS packages; perform data analysis and profiling.

Lead Data Engineer to design, build, and maintain scalable ETL pipelines and cloud data platforms, optimize data models/warehouses, ensure data quality and governance, and collaborate with analytics and business teams.

Operate, monitor and improve production DataOps/ETL workloads for SLHK: manage enterprise schedules and SLAs, lead incident response, execute controlled changes, run data quality checks with evidence, maintain runbooks, and publish/automate service reporting.

Design, develop, and maintain data solutions and applications, ensuring data quality and performance while collaborating with cross-functional teams.