This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Qualified Health is seeking a Data Engineer to support partner integration. This isn't a role where you'll maintain legacy systems or write reports nobody reads. You'll build the data pipelines that directly power AI systems used by clinicians across major U.S. health systems — systems that help doctors identify the right diagnosis, flag patients who need intervention, and improve outcomes at scale. Every query you write, every pipeline you build, directly touches patient care. You'll work in a pod with a Director who owns the customer relationship and 1-2 peers who share the mission. The path from Senior Data Engineer to Director of your own pod is clear and real — we're growing fast enough that the opportunity is a matter of when, not if. Key Responsibilities - Build and maintain data ingestion pipelines that pull from Epic Clarity databases, FHIR APIs, and HL7 feeds into our Databricks lakehouse architecture. - Execute data quality validation and mapping verification for each new workflow deployment. - Support 2-4 health system partners as part of a dedicated integration pod. - Develop and optimize SQL queries against complex healthcare data models. - Contribute to defining reusable data transformation patterns that accelerate future partner onboarding. Qualifications - 4+ years as a data engineer building production ETL/ELT pipelines. - Strong SQL skills (complex joins, window functions, CTEs across large healthcare datasets). - Proficiency with Python and PySpark for data transformation at scale. - Experience with cloud data platforms (Databricks preferred; Snowflake, BigQuery, or Redshift accepted). - Familiarity with FHIR data models or willingness to learn healthcare data standards quickly. - Azure cloud services experience (ADLS Gen2, Key Vault, networking basics). - Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field. Desired Skills - Epic Clarity/Caboodle experience or healthcare data background. - Delta Lake, Delta Sharing, or lakehouse architecture experience. - HL7 message processing or real-time healthcare data pipelines. - Experience working in a multi-tenant SaaS environment. Technical Environment - Azure Databricks + Data Factory (plus Fabric and Snowflake integrations). - PySpark for distributed data processing. - GitHub Actions + Terraform for CI/CD and Infrastructure as Code. - Python with type-safe patterns and modern frameworks. - Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas. What Success Looks Like - High-quality data pipelines delivered on schedule with thorough testing and documentation. - Proactive issue identification with technical problems caught and resolved before impacting partners. - Reusable components that reduce implementation time for subsequent integrations. - Clean production deployments with minimal post-launch issues. - Technical credibility with partner IT teams based on quality of work. - Efficient troubleshooting with quick diagnosis and resolution of data quality issues. Impact & Growth Opportunity As a Data Engineer at Qualified Health, you'll build the data infrastructure that powers AI-driven insights for major health systems. Your work directly enables better patient care by ensuring high-quality, reliable data flows into clinical decision support tools. This role offers deep technical learning in healthcare data, exposure to diverse health system architectures, and growth potential into senior technical or platform architecture roles as we scale. Why Join Qualified Health? - Mission that matters: We partner with the country's leading health systems to safely deploy AI that improves patient care, operational efficiency, and financial performance. - Serious traction: 14+ health system partners including the University of Texas system, University of Rochester Medical Center and Jefferson Health. - Public Benefit Corporation: We're organized to prioritize patient outcomes alongside business performance. - Comp that competes: We offer market competitive base salary, meaningful equity with real upside, and comprehensive benefits. Our Commitment to Diversity Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. Pay & Benefits The pay range for this role is between $155,000 and $190,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits. Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role offers the opportunity to shape and lead the organization’s enterprise data strategy, bridging technical architecture, governance, and team leadership. You will: - Design and maintain robust data pipelines. - Establish a unified enterprise data model. - Enable AI-ready analytics while ensuring data quality and trustworthiness. - Drive impact across multiple functions, including Sales, Marketing, Finance, Delivery, and Product, by providing accurate, actionable insights. - Lead a team of data engineers and analysts. - Mentor stakeholders on data stewardship. - Influence enterprise-wide data governance practices. - Combine hands-on engineering, strategic planning, and cross-functional collaboration in a dynamic, growth-focused environment. - Operate effectively across locations while leading a high-performing data organization. Qualifications - 10+ years of experience in data engineering, including people leadership or functional leadership of data/reporting teams. - 4+ years of hands-on Snowflake expertise, including warehouse design, RBAC, performance tuning, and cost management; Snowflake certification required. - Advanced SQL and proficiency in Python or similar data-oriented languages; experience with dbt, Matillion, Fivetran, Airflow, Prefect, or equivalent tools. - Proven experience leading enterprise reporting, analytics engineering, or data governance initiatives. - Strong knowledge of semantic layers, AI/ML-enabled analytics, and building AI-ready data solutions. - Excellent communication skills with the ability to influence technical and non-technical stakeholders in a matrixed environment. - Preferred: experience in SaaS, education, or services delivery; prior participation in enterprise data strategy or governance councils. Requirements - Architect, build, and maintain scalable ELT/ETL pipelines into Snowflake, ensuring optimized performance, storage, and cost efficiency. - Design enterprise data models, semantic layers, and AI-ready data structures that support reporting, forecasting, and analytics. - Lead and mature the data engineering and reporting team, providing coaching, setting standards, and managing project delivery priorities. - Establish and enforce data governance practices, MDM standards, and data quality controls to ensure consistent, reliable, and trustworthy data. - Partner with cross-functional teams to translate business needs into governed, scalable, and actionable data solutions. - Monitor and optimize pipeline performance, implement automated validation frameworks, and support continuous improvement initiatives. - Drive enterprise adoption of data stewardship, ensuring practical governance practices are embedded into daily workflows. Benefits - Competitive salary range: $135,000–$175,000, based on experience, skills, and internal equity. - Comprehensive health, dental, and vision coverage; 401(k) and paid time off. - Flexible remote work arrangements and professional development opportunities. - Supportive, collaborative environment fostering growth, innovation, and impact. - Opportunity to lead high-visibility initiatives that directly influence organizational success and AI-driven decision-making.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Remitee, a rapidly expanding fintech company specializing in international payments, is seeking a Senior Data Engineer to join its Data Team. We are looking for a highly autonomous builder - someone who can take an ambiguous business problem, design the solution end-to-end, and execute it. This includes data modeling, pipeline development, optimization, and, when necessary, infrastructure setup. This is not a DevOps role. However, we value engineers who are not blocked by infrastructure and can deploy what they need to move forward. Key Responsibilities - Own the end-to-end implementation of data solutions, from problem definition to production deployment. - Design scalable data models and pipelines that support business-critical use cases. - Improve performance, reliability, and cost-efficiency of our Databricks environment. - Lead technical decisions around data architecture and implementation patterns. - Ensure production-grade quality through testing, code review, observability, and monitoring. - Remove blockers independently, including infrastructure setup when necessary. What you’ll build / first 90 days: - Partner with functional teams to clarify requirements and deliver 1–2 high-impact data solutions, running in Databricks and (when needed) cloud services (e.g., functions/jobs). - Review the current data platform (pipelines, tables, costs/performance) and produce a short, actionable improvement plan with clear priorities. - Build and productionize core datasets in Databricks across Bronze/Silver/Gold, including documentation, quality checks, and ownership boundaries. Qualifications - Strong SQL skills (query optimization, partitioning, performance tuning). - Strong Python skills. - Experience building and deploying jobs in Databricks. - Solid understanding of distributed data processing. - Experience working with large datasets. - Ability to independently design and implement end-to-end solutions. - Comfort using Bash and cloud CLIs (AWS/Azure) when needed. Requirements - Infrastructure-as-Code experience (Terraform, ARM, CloudFormation) - Nice to have. - Experience with Docker and CI/CD pipelines - Nice to have. - Experience deploying databases or services in cloud environments - Nice to have. - Experience with NoSQL databases (e.g., MongoDB) - Nice to have. - Understanding of Lakehouse architectures - Nice to have. - Strong system design fundamentals - Nice to have. - Open-source contributions - Nice to have. Company Description Remitee is an international, expanding organization with a vibrant culture that sets us apart. Our work environment is fast-paced and stimulating, offering numerous opportunities for growth and development. If you're a self-starter who thrives in a collaborative and challenging environment, we encourage you to apply. Our company values are fundamental to our daily operations. To succeed here, you'll need to embrace and live our company values: - Build Trust (Integrity and Transparency): Inspire by example, honor your promises, be sincere. - Embrace Diversity (Respect and Empathy): Actively listen and connect with others, value all perspectives. Acknowledge accomplishments, appreciate contributions. - Work in Team (Foster Trust and Collaboration): Create authentic partnerships by offering opportunities and sharing responsibilities. - Focus on Essentials (Be Simple): Make the complex simple by creating effective solutions. Communicate in a clear and easy to understand way. - Be Your Best Self (Excellence): Commit to discipline and perseverance, nurturing both your body and mind. Approach everything you do with passion and purpose.

• Serve as an administrator in Sigma Computing, including managing permissions, access controls, and workspace organization. • Provide daily user support, such as resolving report access issues, helping users understand error messages, and troubleshooting connection or data-source problems. • Participate in an on-call rotation to support the operational reliability. • Assist users with best practices for building reports, organizing content, and using Sigma features effectively. • Conduct demos, training sessions, workshops, and documentation to help teams adopt new features and improve their reporting workflows. • Support onboarding of new users and teams into the BI ecosystem. • Collaborate with analytics, data engineering, and product teams to ensure platform stability and support user needs. • Monitor platform performance, usage patterns, and reliability; escalate or address issues as needed. • Contribute to BI governance efforts, including folder structure, naming conventions, permissions hygiene, and lifecycle management. • Participate in evaluating and rolling out new BI features or enhancements.