Top Data Engineer Jobs in Caloocan

The Data Engineer will design, develop, and optimize big data pipelines using SQL, Python, Spark, Hive, and Hadoop, ensuring data quality and performance.

Lead the data engineering team, overseeing data infrastructure design and management. Collaborate across teams to ensure efficient data handling for analytics and decision-making.

The Data Engineer develops data integration solutions, maintains data systems, collaborates with stakeholders for requirements, and communicates effectively during project delivery.

As a Data Engineer, you will analyze requirements, develop integrations using SQL and Oracle Data Integrator, support audits, and communicate with stakeholders. You'll automate deployments, conduct testing, and work in a team environment.

The Data Engineer will design and develop ETL processes, ensure data quality, report capabilities, and mentor junior team members while delivering data solutions to the business.

The Data Engineer designs and develops ETL processes, analyzes data sources, resolves data quality issues, and mentors junior team members.

The Data Engineer will design and maintain scalable data pipelines, optimize data processing, support analytics, and implement data quality processes.

The Cloud Data Engineer designs and develops data solutions on Azure, implements ETL processes, analyzes data quality, and mentors team members.

The SME, Data Engineer leads a team in developing data solutions, conducting POCs, and ensuring data governance and performance across platforms.

The Data Engineer analyzes raw data, builds data pipelines, combines information from sources, develops analytical tools, and enhances data quality.

A Data Engineer analyzes and organizes raw data, builds data systems, evaluates business needs, and enhances data quality and reliability.

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

The Data Engineer will analyze data, build systems and pipelines, enhance data quality, and develop analytical tools. Requires 3 years experience.

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

As a Data Engineer, you will develop and maintain data infrastructure, lead projects, collaborate with teams to meet data requirements, and implement data quality checks while utilizing various technologies.

The Data Engineer will implement and maintain data workflows, ETL/ELT processes, and pipelines, ensuring quality outputs while collaborating with operations teams for continuous improvement.

Responsible for developing AI models, building data pipelines, optimizing workflows, and deploying cloud solutions for intelligent automation in construction.

Design and implement scalable ETL pipelines using AWS and Python, optimize data solutions, and ensure data quality and compliance.

The Data Engineer will develop ETL processes, maintain data pipelines, perform troubleshooting, and ensure scalable data architecture.

Join Essor's FinTech team as a Data Engineer to manage datasets in Snowflake, ensuring data quality, collaborating with teams, and delivering analytical solutions.

Maintain the reporting data platform by building extraction pipelines in Airflow, transforming data in Snowflake, and managing access controls.

The Cloud Data Engineer designs, builds and maintains scalable data pipelines, implements big data storage formats, and integrates data solutions on AWS with Python, ensuring reliability and scalability.

Develop and implement new features for the Avaloq Data Synthesizer. Maintain the existing product and collaborate with Agile teams on enhancements.

The Senior Backend Engineer designs and builds automated solutions for regulatory reporting, focusing on finance and risk datasets, and collaborates with Business Analysts. Responsibilities include coding, mentoring developers, ensuring system performance, and maintaining software standards.

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