Theoria Medical

Full Time Senior Data Engineer - Remote (PH)

Theoria Medical

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 ₱NaN - ₱100,900 per year

Job Level

Senior

Tech Stack

AirflowApacheAWSAzureDockerETL

About the role

  • Senior Data Engineer
  • Position Type: Full time
  • Compensation: Up to ₱100,900.00
  • Job Location: Remote, PH
  • High Compensation Tied to Business Outcomes: You will be well-rewarded for meeting critical objectives and deadlines.
  • Empowerment & Resources: We will provide the right tools and teams to help you succeed on your own terms.
  • Flexibility & Accountability: You will have autonomy to structure your approach, but must deliver results.
  • Paid Time Off: Relax and recharge with paid vacation and sick leaves.
  • Bonus Boost: Enjoy an extra bonus with our 13th month pay.
  • Health Matters: Get comprehensive HMO coverage upon regularization.
  • Work-Ready: We provide the essential work device for seamless productivity.
  • Work From Home: Enjoy the flexibility and convenience of a fully remote position—work from anywhere in the world without ever needing to commute to an office.
  • Theoria Medical is a comprehensive medical group and technology company dedicated to serving patients across the care continuum.
  • Theoria Medical is a comprehensive medical group and technology company dedicated to serving patients across the care continuum with an emphasis on post-acute care and primary care.
  • We are looking for a highly experienced and detail-oriented Senior Data Engineer to lead the design, development, and optimization of complex data systems. This role is instrumental in building reliable, scalable data pipelines and infrastructure to support advanced analytics and data-driven decision-making across the organization. The ideal candidate is a technical leader with deep expertise in data architecture, performance tuning, and mentoring junior engineers.
  • Shift Structure: Night shift (9 AM to 6 PM EST)
  • Responsibilities:
  • Lead the end-to-end design and development of robust, scalable data pipeline projects across multiple platforms and data sources.
  • Optimize data systems for high performance, reliability, and scalability.
  • Conduct thorough code reviews and provide constructive feedback to ensure best practices and maintain high coding standards.
  • Mentor and guide junior data engineers, supporting their technical growth and development.
  • Collaborate with cross-functional teams to understand data requirements and translate them into efficient engineering solutions.
  • Troubleshoot complex data issues and implement solutions to ensure data quality, availability, and consistency.
  • Primary Focus Areas:
  • Advanced data engineering and pipeline architecture
  • Data performance tuning and system optimization
  • Technical leadership and mentorship
  • Cross-functional collaboration and support
  • Decision-Making Authority:
  • The Senior Data Engineer will independently make technical decisions regarding data system design, architecture, and optimization strategies. They will be responsible for setting engineering standards and determining the best tools and technologies for each project.
  • Communication & Collaboration:
  • This role requires close coordination with the Data Engineering Lead and regular interaction with other technical and business teams to ensure alignment on data needs, project progress, and system design. Strong communication skills are essential to translate complex technical requirements into actionable engineering tasks.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • 5+ years of hands-on experience in data engineering or backend data systems development
  • Data Pipeline Orchestration and Workflow Management
  • Apache Airflow: Popular for scheduling and monitoring complex data pipelines.
  • Prefect: Modern orchestration tool gaining adoption.
  • Apache NiFi, Talend, AWS Glue, Azure Data Factory: ETL tools for data integration and transformation
  • DataDog or similar tools for tracking and monitoring data pipelines
  • DevOps and CI/CD Tools: Docker, Git, CircleCI (or other CI/CD pipelines) for containerization, version control, and automated deployments
  • Experience in building data solutions at enterprise scale