QGenda is hiring a Senior Data Engineer

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. 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