• Design, build, and operate data ingestion and ETL/ELT pipelines for our data systems that power Atto products and customer-facing applications. • Build and maintain our data platform architecture and infrastructure, including data pipelines, warehouses that power analytics and product features and reporting. • Implement data modelling, schema design, and data contracts to make datasets easy to consume. • Introduce and maintain observability, data quality checks, and automated testing for our production data flows. • Driving impact at scale by improving data workflows, service reliability, and making Atto’s capabilities faster, more reliable and widely accessible. • Collaborate with product managers and cross-functional teams to translate market signals and customers’ needs into innovative data-driven solutions. • Create new systems and approaches, while continuously improving and scaling existing ones for performance, reliability, and efficiency. • Conduct deep analysis of transactional datasets to validate data models, surface data quality issues, and propose engineering fixes. • Optimise performance and cost of data processing and storage across cloud services. • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across the business. • Stay current with industry developments, emerging technologies, and best practices in data engineering.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Telematics Data Engineer, you will build and maintain scalable data pipelines on GCP to process high-velocity vehicle telemetry and geospatial data. You will transform raw GPS and CAN-bus signals into high-quality assets using Medallion architectures, with a focus on integrating Map APIs (e.g., Google Maps Platform) to provide critical spatial context. You will implement robust CI/CD workflows and data governance practices to ensure the data platform remains secure, efficient, and available for downstream analytics. Key Pillars - Geospatial Integration: Implementing Google Maps APIs and spatial libraries to enrich raw telemetry with reverse geocoding, route-matching, and points of interest. - Operational Execution: Utilizing Terraform, Git, and Airflow to deploy and manage reproducible, cost-optimized cloud infrastructure. - Data Quality: Maintaining data lineage, PII protection (location privacy), and observability to ensure high-trust vehicle data assets. - Cross-Functional Support: Working alongside Data Scientists and Product Managers to deliver clean datasets for vehicle health and driver behavior insights. - Technical Development: Building ETL/ELT pipelines for spatial indexing and supporting the migration of data assets to BigQuery. Qualifications - Experience with GCP and data pipeline development. - Proficiency in Python or similar programming languages. - Familiarity with data governance and CI/CD practices. - Understanding of geospatial data and APIs. Requirements - Strong analytical and problem-solving skills. - Ability to work collaboratively in a team environment. - Excellent communication skills. - Experience with Terraform, Git, and Airflow. Benefits - Competitive salary and performance-based bonuses. - Comprehensive health benefits. - Retirement savings plans with company match. - Opportunities for professional development and growth.

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 Integration Engineer to serve as the technical implementation specialist for our healthcare data integration initiatives. In this hands-on role, you'll design and build robust data pipelines that transform raw healthcare data from diverse sources (Epic, LIMS, PACS, SharePoint, etc.) into production-ready datasets powering our AI platform. Your roles are complementary: - You own: Technical implementation, ETL development, data quality validation, pipeline construction, troubleshooting, and production deployment execution. - Manager owns: Partner relationships, requirements gathering, timeline management, stakeholder communication, issue escalation, and ensuring delivery meets expectations. - Together you deliver: Successful data integrations that meet partner needs on time with high quality. This is a technical role for someone who loves working with data, enjoys solving puzzles, and takes pride in building reliable, production-grade solutions. Qualifications - 5+ years of experience in data analytics, data engineering, or solution delivery roles, with demonstrated expertise in data integration and ETL processes. - Strong analytical toolkit with proficiency in: - PySpark for distributed data processing - Advanced SQL for data querying and transformation - Excel for data analysis and reporting - Production ETL experience: Track record of building and maintaining production-grade data pipelines with proper error handling and monitoring. - Data quality focus: Experience implementing validation frameworks and troubleshooting data quality issues. - Healthcare data experience: Prior work with healthcare datasets (EHR, claims, clinical, lab data). - Problem-solving mindset: Ability to independently diagnose and resolve complex technical issues. - Attention to detail: Commitment to accuracy, testing, and delivering reliable solutions. - Collaborative working style: Comfortable partnering with non-technical colleagues and adapting to feedback. - Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field. - Ability to work onsite in Houston, TX 2-3 days/week. Requirements - Epic Clarity experience: Direct work with Epic's relational database structure and clinical data models. - Healthcare data standards knowledge: Understanding of FHIR, HL7v2, DICOM, LOINC, SNOMED, ICD-10. - Azure cloud platform: Hands-on experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake. - Healthcare compliance awareness: Understanding of HIPAA requirements and healthcare data security best practices. - Data warehouse/lakehouse experience: Familiarity with dimensional modeling and modern data architecture patterns. - DevOps practices: Experience with Git, CI/CD pipelines, and infrastructure-as-code. - Performance tuning: Proven ability to optimize complex data transformations for scale. - LIMS/PACS experience: Prior work integrating laboratory or imaging systems data. - Multiple data format fluency: Experience with JSON, XML, Parquet, CSV, and other healthcare interchange formats. Benefits - Competitive salaries with equity packages. - Robust medical/dental/vision insurance. - Flexible working hours. - Hybrid work options. - An inclusive environment that fosters creativity and innovation. Company Description 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. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status. The pay range for this role is between $130,000 and $180,000, 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.

• Deliver data solutions for client projects to produce positive outcomes • Collaborate with other team members to engineer data outcomes for clients • Support a Microsoft Fabric-first approach and medallion architecture • Ingest, organize, transform, and analyze raw data with business goals in mind • Improve data quality and efficiency while maintaining datasets • Understand and leverage client standards, processes, and recommended approaches • Identify and suggest opportunities for data process improvements and efficiencies • Ensure data readiness for analytics, AI, or other outcomes • Support agile work processes and keep work management systems current (i.e., Azure DevOps) • Document client work appropriately • Complete development within service-level agreements and cycle time expectations • Manage various work projects to meet client high-quality standards • Perform QA on your work and that of teammates to ensure the best outcomes • Embody client core values