Vertere Global Solutions, Inc.
Data Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Mandaluyong City, Metro Manila, Philippines
Work mode:
Onsite
Published on:
10 September 2026
What they need
DATA ENGINEER
JOB SUMMARY
We are seeking a highly skilled Data Engineer to design, build, and maintain scalable data solutions that support business intelligence, analytics, and machine learning initiatives. The ideal candidate will have experience developing robust data pipelines, optimizing data architectures, ensuring data quality, and collaborating with cross-functional teams to deliver reliable and efficient data platforms.
KEY RESPONSIBILITIES:
Data Pipeline Development
- Design, develop, and maintain scalable ETL/ELT pipelines for processing and integrating data from multiple sources.
- Ensure reliable and efficient movement of data across enterprise systems.
Data Architecture
- Design and implement scalable data warehouses, data lakes, and lakehouse architectures.
- Support the organization's evolving data needs through modern and efficient data platforms.
Data Quality & Governance
- Implement automated data validation, cleansing, monitoring, and quality assurance processes.
- Ensure data integrity, consistency, security, and compliance with organizational standards.
Performance Optimization
- Troubleshoot and optimize slow-running queries, data processing jobs, and pipeline performance.
- Continuously improve system efficiency, scalability, and reliability.
Collaboration & Support
- Work closely with data analysts, data scientists, software engineers, and other stakeholders to deliver clean, accessible, and trusted datasets.
- Support analytics and machine learning teams by ensuring data availability and readiness.
- Promote best practices in data engineering, governance, and security.
TECHNICAL QUALIFICATIONS
REQUIRED SKILLS
- Strong proficiency in Python, SQL, and either Scala or Java.
- Hands-on experience building and maintaining ETL/ELT data pipelines.
- Experience with cloud data platforms, particularly:
- AWS (Glue, EMR, Redshift)
- Exposure to Azure (Synapse, Data Factory) and/or Google Cloud Platform (BigQuery, Dataproc) is an advantage.
- Experience with big data technologies such as:
- Apache Spark
- Apache Flink
- Hadoop
- Strong knowledge of data modeling methodologies, including:
- Kimball Methodology
- Star Schema
- Snowflake Schema
- Data Vault
- Experience with workflow orchestration tools such as:
- Apache Airflow
- Prefect
- Dagster
- Familiarity with DevOps/DataOps practices, including:
- Git
- CI/CD Pipelines
- Terraform
- CloudFormation
PREFERRED CERTIFICATIONS
- AWS Certified Data Engineer
- Google Professional Data Engineer
- Microsoft Azure Data Engineer Associate
- Other relevant cloud or data engineering certifications
SOFT SKILLS
- Excellent verbal and written communication skills.
- Strong analytical, critical thinking, and problem-solving abilities.
- Exceptional attention to detail and commitment to data accuracy.
- Effective time management and prioritization skills.
- Ability to collaborate across multiple IT and business teams.
- Strong understanding of information security, data privacy, and governance standards.
- Continuous learner with a passion for emerging technologies and industry trends.
- Experience in healthcare analytics is a plus.
QUALIFICATIONS
- Bachelor's degree in Engineering, Management Information Systems, Computer Science, Information Technology, or other related Science and Technology disciplines.
- Minimum of 3 to 5 years of relevant experience in Data Engineering or a similar role.
- Proven experience designing and supporting enterprise-scale data solutions.
PREFERRED INDUSTRY BACKGROUND
Candidates from the following industries are highly encouraged to apply:
- Technology and Software Companies
- Consulting and Professional Services Firms
- Telecommunications
- Multinational Corporations
- Large Local Conglomerates
- Healthcare Technology Organizations
Why Join Us?
- Work with cutting-edge cloud and big data technologies.
- Collaborate with high-performing analytics, engineering, and data science teams.
- Drive data-driven decision-making across the organization.
- Contribute to innovative projects involving modern data platforms, automation, and AI-driven solutions.
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