Top Data Engineer Jobs in Caloocan

Design, build, and maintain data storage, ingestion and transformation pipelines. Optimize jobs, automate processes, perform unit and integration testing, monitor platform stability, ensure governance and security compliance, collaborate with stakeholders, document processes, run POCs, and contribute to team best practices to support analytics and data engineering needs.

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

Design, implement, and maintain scalable data infrastructure for analytics and operational decision-making, optimizing data pipelines and ensuring data quality.

Design, build, and maintain end-to-end analytics and reporting solutions: ingest, transform, model, and store data; build Cognos and Power BI reports; ensure data quality; analyze datasets and present insights to stakeholders.

Data Engineer II will execute data project initiatives, maintain data applications, automate processes, and mentor junior developers while collaborating with teams.

Design, build, test and maintain ETL pipelines using Python and Jupyter notebooks. Transform vendor and client data, migrate Excel logic to Python, document processes, respond to incidents within SLAs, automate processes, and collaborate with business and technical teams to improve data workflows.

Design, develop, and maintain complex T-SQL stored procedures and SSIS ETL packages; performance tune databases; perform data analysis, validation, and testing; support production data loads and troubleshoot database issues while collaborating with technical and business teams.

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.

Lead design and delivery of analytics, automation, and AI-enabled data solutions to improve operational efficiency across Asia Pacific. Build data pipelines, models, dashboards, desktop apps and Excel add-ins; advise stakeholders, manage projects, establish standards, and coach junior team members.

The Cloud Data Test Engineer will test cloud-based data solutions, ensure data pipeline quality, perform end-to-end data validation, and create test plans.

Design, develop, and maintain scalable ELT/ETL data pipelines and reusable data models using Azure Data Factory, dbt, Snowflake, SQL, and Python. Collaborate with Marketing and business stakeholders to translate requirements, ensure data quality, optimize Snowflake performance, monitor production pipelines, maintain documentation and data lineage, and mentor junior engineers.

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.

Senior Data Engineer responsible for designing, building, and operating Enterprise Data Lake solutions. Implement ETL/ELT using Spark/Python and Azure services, monitor platform performance, perform POCs, support business users, handle incidents/changes, write documentation, execute tests and platform updates, and support agile delivery squads.

Design and implement scalable data and AI solutions. Build and optimize EL(T) pipelines, manage data extraction/integration/storage, apply software engineering best practices, mentor team members, collaborate with stakeholders, and drive AI/data platform adoption across projects.

Lead technical delivery of large-scale data platform and BI solutions: gather requirements from clients, design and implement data platforms, build ETL/ELT pipelines, perform data modelling and SQL performance tuning, provide documentation, training and knowledge transfer, and advise on profiling, integration and platform performance/cost.

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.

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.

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.

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.

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, 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.

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.