Senior Data Engineer

waystar; Duluth (GA); On-site; USD 130,000 - 180,000; Full time

Job summary

Waystar in Duluth, GA is seeking a Senior Data Engineer to join our Business Data & Architecture team and accelerate our Data Modernization on Google Cloud Platform (GCP). This is a hands-on senior IC role focused on scalable data platforms, ELT development, and analytics enablement.

You will design, build, and optimize data pipelines using BigQuery, Fivetran, APIs, and Python, with dbt models and medallion architecture.

Qualifications

• Bachelor's degree in computer science, information systems, data engineering, or related field.
• 5+ years of experience in Data Engineering or related technical discipline.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Advanced expertise in BigQuery.
• Strong experience with dbt and modern ELT development practices.
• Advanced SQL development and query optimization skills.
• Strong Python programming experience.
• Experience building scalable data pipelines and transformation frameworks.
• Experience working with APIs and data integration patterns.
• Experience with workflow orchestration tools such as Airflow or Cloud Composer.
• Experience with GitHub, source control, and CI/CD development practices.
• Strong understanding of dimensional modeling and analytics engineering concepts.
• Strong troubleshooting, problem-solving, and analytical skills.
• Excellent communication and collaboration skills.

Responsibilities

• Design, build, and maintain scalable ELT pipelines into BigQuery using Fivetran, APIs, Python, and cloud-native services.
• Develop and optimize bronze, silver, and gold data layers following Medallion Architecture principles.
• Create and maintain reusable dbt models that support enterprise reporting, analytics, and self-service use cases.
• Design and implement scalable ingestion patterns for structured and semi-structured data.
• Troubleshoot and resolve complex data pipeline, transformation, and performance issues.
• Improve pipeline reliability, performance, scalability, and maintainability.
• Design and implement scalable data models supporting business intelligence, analytics, and operational reporting.
• Partner with business analysts, product owners, and stakeholders to translate requirements into technical solutions.
• Develop reusable business-focused datasets and metrics aligned with enterprise standards.
• Support semantic modeling and reporting initiatives across business domains.
• Contribute to standardization of enterprise metrics and reporting assets.
• Implement automated data validation, testing, and data quality checks.
• Develop monitoring, alerting, and observability capabilities across the data platform.
• Investigate and resolve data anomalies, processing issues, and performance bottlenecks.
• Support operational excellence through logging, incident analysis, and root cause investigations.
• Ensure data consistency, accuracy, and reliability across ingestion and transformation processes.
• Develop and maintain orchestration workflows using Cloud Composer (Managed Airflow).
• Contribute to CI/CD pipelines using GitHub and modern deployment practices.
• Support Infrastructure-as-Code initiatives using Terraform and platform automation tools.
• Improve engineering efficiency through automation, reusable components, and standard development patterns.
• Participate in platform optimization and modernization initiatives.
• Support data classification, lineage, metadata management, and governance initiatives.
• Implement secure access controls and data protection practices aligned with enterprise standards.
• Partner with Data Governance teams to improve data discoverability and trust.
• Ensure compliance with regulatory, privacy, and security requirements.
• Contribute to documentation and operational standards for enterprise data assets.
• Collaborate with engineers, architects, analysts, and business stakeholders across multiple domains.
• Participate in technical design reviews and engineering discussions.
• Perform peer code reviews and support engineering quality standards.
• Contribute to documentation, knowledge sharing, and reusable engineering practices.
• Evaluate new technologies and recommend platform improvements where appropriate.

Skills

GCP experience

BigQuery

dbt

SQL

Python

APIs

Airflow/Cloud Composer

GitHub/CI-CD

Dimensional modeling

Education

Bachelor's degree in CS/IS/Data Engineering or related field

Tools

Terraform

Cloud Composer

Airflow

GitHub

CI/CD

Job description

ABOUT THIS POSITION

Waystar is seeking a highly skilled Senior Data Engineer to join our Business Data & Architecture team and help advance our enterprise Data Modernization Program on Google Cloud Platform (GCP).

This is a senior individual contributor role focused on designing, building, and optimizing scalable data solutions that enable analytics, reporting, governance, and AI initiatives across the enterprise. The ideal candidate is a hands‑on engineer with deep technical expertise in cloud data platforms, data modeling, ELT development, and modern engineering practices.

You will work across the full data lifecycle, from data ingestion and transformation to orchestration, quality, observability, and governance, helping deliver trusted and scalable data products that support business decision-making.

WHAT YOU'LL DO

Data Pipeline Development & Optimization

• Design, build, and maintain scalable ELT pipelines into BigQuery using Fivetran, APIs, Python, and cloud-native services
• Develop and optimize bronze, silver, and gold data layers following Medallion Architecture principles
• Create and maintain reusable dbt models that support enterprise reporting, analytics, and self-service use cases
• Design and implement scalable ingestion patterns for structured and semi-structured data
• Troubleshoot and resolve complex data pipeline, transformation, and performance issues
• Improve pipeline reliability, performance, scalability, and maintainability

Data Modeling & Analytics Enablement

• Design and implement scalable data models supporting business intelligence, analytics, and operational reporting
• Partner with business analysts, product owners, and stakeholders to understand and translate requirements into technical solutions
• Develop reusable business-focused datasets and metrics aligned with enterprise standards
• Support semantic modeling and reporting initiatives across business domains
• Contribute to the standardization of enterprise metrics and reporting assets

Data Quality, Observability & Reliability

• Implement automated data validation, testing, and data quality checks
• Develop monitoring, alerting, and observability capabilities across the data platform
• Investigate and resolve data anomalies, processing issues, and performance bottlenecks
• Support operational excellence through logging, incident analysis, and root cause investigations
• Ensure data consistency, accuracy, and reliability across ingestion and transformation processes

Platform Engineering & Automation

• Develop and maintain orchestration workflows using Cloud Composer (Managed Airflow)
• Contribute to CI/CD pipelines using GitHub and modern deployment practices
• Support Infrastructure-as-Code initiatives using Terraform and platform automation tools
• Improve engineering efficiency through automation, reusable components, and standard development patterns
• Participate in platform optimization and modernization initiatives

Data Governance & Security

• Support data classification, lineage, metadata management, and governance initiatives
• Implement secure access controls and data protection practices aligned with enterprise standards
• Partner with Data Governance teams to improve data discoverability and trust
• Ensure compliance with regulatory, privacy, and security requirements
• Contribute to documentation and operational standards for enterprise data assets

Collaboration & Continuous Improvement

• Collaborate with engineers, architects, analysts, and business stakeholders across multiple domains
• Participate in technical design reviews and engineering discussions
• Perform peer code reviews and support engineering quality standards
• Contribute to documentation, knowledge sharing, and reusable engineering practices
• Evaluate new technologies and recommend platform improvements where appropriate

WHAT YOU'LL NEED

• Bachelor's degree in computer science, Information Systems, Data Engineering, or a related field
• 5+ years of experience in Data Engineering or a related technical discipline
• Strong hands‑on experience with Google Cloud Platform (GCP)
• Advanced expertise in BigQuery
• Strong experience with dbt and modern ELT development practices
• Advanced SQL development and query optimization skills
• Strong Python programming experience
• Experience building scalable data pipelines and transformation frameworks
• Experience working with APIs and data integration patterns
• Experience with workflow orchestration tools such as Airflow or Cloud Composer
• Experience with GitHub, source control, and CI/CD development practices
• Strong understanding of dimensional modeling and analytics engineering concepts
• Strong troubleshooting, problem‑solving, and analytical skills
• Excellent communication and collaboration skills

Preferred Qualifications

• Experience supporting enterprise‑scale data modernization programs
• Experience migrating workloads from Snowflake, Azure, SQL Server, Teradata, or other platforms to BigQuery
• Experience with Terraform and Infrastructure-as-Code practices