Senior Data Engineer — GCP, BigQuery & ELT Expert

Waystar; Louisville (KY); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive pay

Benefits package

Paid time off

Parental leave

Education support

LinkedIn Learning

Mental health programs

401K match

Pet insurance

ERGs

Job summary

Waystar seeks a Senior Data Engineer to advance our enterprise Data Modernization on Google Cloud Platform. You will design, build, and optimize scalable data solutions across ingestion, transformation, and governance to enable analytics, reporting, and AI initiatives enterprise-wide.

You will champion medallion data layers, reusable dbt models, and robust observability while collaborating with analysts, product owners, and stakeholders to deliver trusted data products that power business

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 BI, analytics, and reporting
• Partner with analysts and stakeholders to translate requirements into technical solutions
• Develop reusable datasets and metrics aligned with enterprise standards
• Support semantic modeling and reporting initiatives across domains
• Contribute to standardization of enterprise metrics and reporting assets
• Implement automated data quality checks and observability capabilities
• Develop monitoring and alerting across the data platform
• Investigate data anomalies and performance bottlenecks
• Ensure data consistency, accuracy, and reliability across ingestion and transformation processes
• Develop orchestration workflows using Cloud Composer and CI/CD pipelines using GitHub
• Support Infrastructure-as-Code initiatives using Terraform
• Improve engineering efficiency through automation and reusable components
• Participate in platform optimization and modernization initiatives
• Support data governance and security initiatives

Skills

GCP

BigQuery

dbt

Python

SQL

GitHub

Cloud Composer

Cloud Functions

REST APIs

Fivetran

Airflow

CI/CD

Terraform

Dataplex

Knowledge Catalog

Cloud Run

Snowflake

Azure Data Factory

Education

Bachelor's degree in CS/IS/Data Engineering

Tools

GitHub

Airflow/Cloud Composer

Fivetran

dbt Cloud

Job description

Waystar seeks a Senior Data Engineer to advance our enterprise Data Modernization on Google Cloud Platform. You will design, build, and optimize scalable data solutions across ingestion, transformation, and governance to enable analytics, reporting, and AI initiatives enterprise-wide.

You will champion medallion data layers, reusable dbt models, and robust observability while collaborating with analysts, product owners, and stakeholders to deliver trusted data products that power business