Sr. Data Engineer

Work Setup:

• Hybrid (3x onsite per week in Makati)
• Dayshift
• Fixed weekends off

Qualifications:

Required Qualifications:

• 6–8 years of experience in Data Engineering or related roles (3+ years may be considered)
• Strong hands-on expertise with dbt (Data Build Tool) for data transformation, testing, and modeling
• Experience orchestrating and managing workflows using Argo Workflows in Kubernetes environments
• Strong hands-on experience with Kubernetes, including pod execution, resource management, monitoring, and debugging
• Experience designing, building, and maintaining ELT/ETL data pipelines in cloud-native environments
• Strong proficiency in Python and/or Shell scripting for automation and data engineering workflows
• Advanced SQL skills for data transformation, optimization, validation, and data modeling
• Hands-on experience with cloud platforms and storage technologies including AWS, S3, Redshift, Snowflake, or similar technologies
• Familiarity with CI/CD pipelines, Git-based version control, and infrastructure-as-code concepts
• Strong understanding of data warehousing principles, dimensional modeling, and ELT architectures
• Experience troubleshooting data pipeline failures, performance bottlenecks, workflow issues, and infrastructure-related issues
• Strong analytical, problem-solving, and communication skills
• Ability to collaborate effectively with cross-functional stakeholders, including analytics, business, and engineering teams
• Experience working within established engineering standards, coding guidelines, and data governance practices

Preferred / Nice-to-Have Qualifications:

• Experience running dbt on Kubernetes using Argo Workflows or similar orchestration platforms
• Exposure to modern cloud-native observability tools (logging, monitoring, alerting)
• Experience with modern data warehouses such as Snowflake, BigQuery, or Redshift
• Knowledge of data governance, metadata management, access control, and compliance practices
• Familiarity with data visualization/reporting tools such as Power BI, Tableau, or Looker
• Cloud certifications in AWS, GCP, or Kubernetes
• Experience supporting analytics, reporting, or downstream data consumer requirements

Job Responsibilities:

• Design, develop, and maintain scalable ELT/ETL pipelines using dbt for data transformation and modeling
• Build and operate cloud-native data pipelines running in Kubernetes environments, ensuring reliability, scalability, and observability
• Orchestrate and manage data workflows using Argo Workflows in Kubernetes-based platforms
• Collaborate with analytics, business, and engineering teams to translate requirements into well-modeled datasets and scalable solutions
• Implement data quality checks, testing, monitoring, and validation within dbt and orchestration workflows
• Optimize performance of data transformations, SQL queries, workflows, and pipeline executions
• Troubleshoot and resolve pipeline failures, infrastructure issues, performance bottlenecks, and orchestration errors
• Support CI/CD practices for data pipelines and dbt deployments using Git-based workflows and existing templates
• Participate in code reviews, technical documentation, and knowledge-sharing activities across the team
• Ensure adherence to data governance, compliance, security, and engineering best practices
• Support monitoring, logging, and observability efforts to improve platform stability and reliability
• Contribute to continuous improvements in data architecture, automation, and engineering standards