Data Engineer

Magnustech Solutions Inc; Makati; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Magnustech Solutions Inc. is seeking an senior data engineering leader to drive end-to-end delivery of complex data and analytics solutions within a cloud-first environment.

You will design scalable pipelines, ensure data quality and governance, and collaborate with stakeholders to translate requirements into robust architectures. You will mentor engineers, conduct reviews, and optimize pipelines for performance, reliability, and cost.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field.
• Deep experience with data transformation, ETL/ELT, and data management.
• Deep experience in writing and optimizing complex SQL.
• Experience with data modeling using dimensional modeling techniques, including star schemas.
• Experience with cloud infrastructure, cloud computing, and big data platforms.
• Understanding of structured, semi-structured, and unstructured data.
• Experience with data streaming, messaging, and event-driven data architecture.
• Knowledge of data governance and data quality frameworks.
• Experience working in an Agile environment.
• Experience working with NoSQL databases, such as graph, document, and column databases.
• Knowledge of machine learning and artificial intelligence concepts.
• Ability to articulate ideas with strong communication and presentation skills.
• Ability to work as part of a small team, share ideas, and contribute to strategic goals.

Responsibilities

• Lead end-to-end technical delivery of data and analytics solutions.
• Design, build, and optimize data pipelines and analytical data models.
• Assess source systems and data quality; define transformations and data standards.
• Partner with stakeholders to translate requirements into designs and delivery plans.
• Drive data architecture, best practices, and cost-efficient cloud usage.
• Mentor team members and provide hands-on support.
• Perform code and design reviews to ensure quality and performance.
• Lead root cause analysis and implement preventative improvements.
• Improve delivery processes to increase speed and reliability.
• Implement data governance: lineage, quality checks, and secure handling.
• Collaborate with platform/infrastructure teams on cloud data platforms (Snowflake, Azure).
• Support DevOps/CI/CD for data engineering with automated tests and pipelines.
• Ensure operational excellence: monitoring, alerts, and SLAs for pipelines and products.
• Contribute to platform strategy and tool selection for self-service enablement.

Skills

Data transformation

ETL/ELT

SQL optimization

Data modeling

Cloud infrastructure

Data governance

Agile

NoSQL databases

Machine learning concepts

Communication skills

Education

Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field

Job description

• Lead end-to-end technical delivery of complex data and analytics solutions, ensuring scalability, reliability, and alignment to business outcomes.
• Design, build, and optimize data pipelines and analytical data models (batch and near real-time) to support enterprise reporting, BI, and advanced analytics use cases.
• Assess source systems and data quality, defining transformation logic, data standards, and controls to meet business definitions and governance requirements.
• Partner with business and technical stakeholders to translate requirements into technical designs, and contribute to estimation, planning, and delivery sequencing.
• Drive data architecture and engineering best practices, including modular design, reusability, performance optimization, and cost efficiency.
• Mentor and coach team members, elevating overall engineering capability through guidance, knowledge sharing, and hands-on support.
• Perform code and design reviews, ensuring adherence to standards, maintainability, and optimal performance of data solutions.
• Lead root cause analysis and issue resolution, implementing preventative measures and performance improvements across pipelines and platforms.
• Continuously improve delivery processes, identifying opportunities to increase speed, quality, automation, and reliability.
• Implement and enforce data governance practices, including lineage, documentation, data quality checks, and secure data handling.
• Collaborate with platform and infrastructure teams to ensure optimal use of cloud data platforms (e.g., Snowflake, Azure), including performance tuning and cost management.
• Support DevOps and CI/CD practices for data engineering, including automated testing, deployment pipelines, and environment management.
• Ensure operational excellence, including monitoring, alerting, and SLAs for critical data pipelines and data products.
• Contribute to platform strategy and tool selection, evaluating new technologies to enhance data engineering capabilities and self-service enablement.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• Deep experience with data transformation, ETL/ELT, and data management.
• Deep experience in writing and optimizing complex SQL.
• Experience with data modeling using dimensional modeling techniques, including star schemas.
• Experience with cloud infrastructure, cloud computing, and big data platforms.
• Understanding of structured, semi-structured, and unstructured data.
• Experience with data streaming, messaging, and event-driven data architecture.
• Knowledge of data governance and data quality frameworks.
• Experience working in an Agile environment.
• Experience working with NoSQL databases, such as graph, document, and column databases.
• Knowledge of machine learning and artificial intelligence concepts.
• Ability to articulate ideas with strong communication and presentation skills.
• Ability to work as part of a small team, share ideas, and contribute to strategic goals.