Senior Data Engineer

This is a remote position.

Responsibilities:

• Own data pipeline development: Design, develop, and maintain reliable ETL/ELT pipelines for ingesting, transforming, and delivering large-scale datasets across multiple platforms and sources.
  

• Lead technical design: Define processing logic, data models, integration approaches, and workflow dependencies, considering scalability, maintainability, security, and cost.
  

• Develop and optimize data processing: Write efficient SQL, Hive queries, and Python code. Apply distributed processing frameworks such as Spark where appropriate.
  

• Build and manage AWS workflows: Develop and support data solutions using Amazon S3, Athena, EC2, and EMR, including monitoring and resource optimization.
  

• Manage workflow orchestration: Build and maintain automated workflows using Apache Airflow or comparable orchestration tools, including scheduling, dependencies, retries, alerting, and recovery.
  

• Ensure production reliability: Monitor pipeline performance and data freshness, investigate failures, perform root cause analysis, and implement improvements that prevent recurring issues.
  

• Maintain data quality and governance: Establish validation checks, reconciliation processes, lineage documentation, and appropriate access controls throughout the data lifecycle.
  

• Lead and mentor a small team: Guide 2-3 engineers, break requirements into actionable tasks, review code and designs, support troubleshooting, and track delivery commitments.
  

• Collaborate with stakeholders: Work closely with analytics, product, engineering, and data science teams to clarify requirements, agree on priorities, communicate progress, and manage dependencies.
  

• Maintain technical documentation: Create and update solution designs, data flow diagrams, data dictionaries, operating procedures, and support runbooks using Confluence or similar platforms.
  

• Apply AI to engineering workflows: Identify practical opportunities to use AI for development, documentation, troubleshooting, and automation. Build simple AI agents and validate their outputs before operational use.
  

• Support agile delivery: Manage work through Jira, contribute to sprint planning and technical reviews, and coordinate across regions and work schedules as required.
  

Requirements

Requirements:

• 5+ years of professional experience in data engineering, with demonstrated ownership of production data pipelines and large-scale data processing.
  

• Strong SQL expertise, including complex joins, window functions, transformations, query tuning, and troubleshooting.
  

• Strong working knowledge of Hive and the Hadoop ecosystem, including partitioning, storage formats, and distributed data processing concepts.
  

• Proficiency in Python for data processing, automation, integration, and maintainable production code.
  

•  Hands-on experience with Amazon S3, Athena, EC2, and EMR.
  

• Strong experience with Apache Airflow or another ETL/workflow orchestration tool, with Airflow preferred.
  

• Experience implementing data quality checks, monitoring, error handling, and operational support processes.
  

• Ability to translate business requirements into technical designs and deliver solutions with minimal supervision.
  

•  Strong documentation and communication skills, including the ability to explain technical issues clearly to business and technical stakeholders.
  

• Working experience with Jira and Confluence for task tracking, delivery coordination, and documentation.
  

• Practical understanding of AI capabilities and limitations, along with hands-on experience creating simple AI agents or AI-assisted automations.
  

•  Experience with version control, code reviews, and collaborative development practices.
  

Preferred Qualifications

• Hands-on experience with Apache Spark using PySpark or Scala.
  

• Experience with Snowflake, including data transformation, query optimization, and integration with cloud data pipelines.
  

• Practical experience using OpenAI Codex for engineering tasks and Snowflake Cortex for AI-enabled data workflows.
  

• Previous experience mentoring engineers, leading technical delivery, or managing a small team. Formal people management experience is an added advantage.
  

• Experience supporting marketing technology, audience data, campaign reporting, or customer analytics.
  

Benefits

What we offer:

• Competitive Salary Package: Receive a pay package that matches your skills and experience.
  

• Vacation and Sick Leave credits: Enjoy vacation and sick leave credits to maintain work-life balance.
  

• Health Coverage: Get medical, dental, and vision insurance for you and your dependents.
  

• Government-Mandated Benefits: Full coverage of all statutory benefits like SSS, PhilHealth, and Pag-IBIG.
  

• Learning Opportunities: Access training, certifications, and mentorship to grow your career.
  

• Team Engagement: Join team-building activities and wellness programs.
  

• Modern Tools: Use the latest technology to excel in your role.
  

• Career Growth: Clear paths for promotion and professional development.
  

• Inclusive Culture: Be part of a diverse, supportive, and collaborative global team.