Senior Data Engineer
Qgenda · Atlanta, Georgia · Posted Jun 25, 2026
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Who We Are
QGenda is redefining healthcare workforce management everywhere care is delivered. We're on a mission to empower the healthcare industry to better onboarding, deploy, and manage their workforce. Over 4,500 healthcare organizations have trusted us to help them make strategic workforce decisions through our unified software platform. With more than 800 employees across the US, we are united in our vision and culture to make a difference for our customers, while enjoying the day-to-day.
At QGenda, we value our employees and their contributions toward the success of the business. We strive to create a dynamic work environment that fosters growth, innovation, and collaboration, where employees can be proud of the work they do and the impact it has on the healthcare industry.
QGenda is headquartered in Atlanta.
To learn more about QGenda, visit us at qgenda.com or follow us on Instagram or LinkedIn .
About Your Role
As a Senior Data Engineer, you will design, build, and optimize the data platform, including pipelines, models, and infrastructure that power analytics, reporting, and data-driven decision making across the QGenda product lines. You will serve as a technical leader with the team, contributing to architectural direction, driving best practices, and supporting complex data initiatives. This role requires deep technical expertise, strong cross-functional collaboration, and the ability to deliver scalable, high-performing data systems that meet evolving business needs.
How You’ll Make an Impact
Deliver High-Quality, Scalable Data Engineering Solutions
Architect, develop, test, and maintain ELT/ETL pipelines and data workflows supporting high-volume analytics
Implement advanced data processing solutions and observability techniques to ensure data is accurate, fresh, and reliable
Design and refine data models and semantic layers that support analytical self-service and advanced reporting.
Build data visualizations and dashboards supporting analytics use cases
Strengthen Data Engineering Practices and Technical Standards
Translate complex business and analytics requirements into efficient, scalable data solutions
Apply best practices for version control, documentation, CI/CD, Infrastructure as Code, and data governance
Participate in code reviews, identify opportunities for architectural improvement,, and contribute to continuous improvement efforts
Collaborate Across Teams
Partner with data engineers, DBAs, managers, and business stakeholders to deliver high-impact data products
Provide technical guidance, informal mentorship, and support to other engineers in order to elevate team capabilities
Communicate technical decisions, risks, and recommendations to both technical and non-technical audiences
Drive Technical Excellence
Optimize data pipelines and warehouse performance for speed, cost, and scalability
Evaluate, prototype, and influence adoption of new tools, frameworks, and architectural patterns that enhance the data platform
Contribute to data observability, incident response, and root-cause analysis for complex data issues
Design and deliver AI-ready data products, ensuring data structures, metadata, and pipelines are suitable for natural language processing, predictive analytics, and other AI-driven capabilities
Who You Are
Exceptional analytical, problem solving, and debugging skills
Strong communication with the ability to simplify and articulate technical concepts
Ability to work collaboratively, influence architecture, and take ownership of deliverables
Commitment to quality, reliability, and continuous improvement
Experience You Bring
5-7+ years in data engineering/analytics engineering, or related field
Bachelor’s degree specializing in computing, data engineering, or related discipline
Expertise in distributed data processing, data modeling, and performance tuning
Strong proficiency in SQL and Python
Experience with modern data stack components, such as:
Cloud: AWS, GCP, Azure
Warehouses: Snowflake, Redshift, BigQuery, etc.
Orchestration: Airflow, MWAA, Composer, etc.
Transformation: dbt, etc.
Observability: data lineage/monitoring tools
BI: Looker, Tableau, Power BI, etc.
DevOps: Git, CI/CD, Terraform/CloudFormation
Not Required, But Nice to Have
Experience preparing datasets and data structures for AI/ML use cases, including NLP-driven analytics
Experience with Glue, Dataflow
#LI-Hybrid
Applicants for this position must be authorized to work for any employer in the United States (U.S.), including being located in the US. We are unable to sponsor, take over sponsorship of, or hire candidates with an employment visa at this time.
What’s In It For You
We offer a comprehensive total rewards package to support our full-time employees and their family’s day-to-day needs, well-being and major life events, which includes:
Fully company-paid options for medical (both in-person and virtual), dental and vision insurance
Generous paid time…