Smarter Technologies is the automation and insight platform for healthcare efficiency. As a leading AI-powered revenue cycle management (RCM) platform, we combine proprietary agentic agents, human-in-the-loop AI agents, clinical ontology, and global financial and administrative services. Our comprehensive platform empowers healthcare organizations to automate the entirety of their administrative and financial workflows—driving operational optimization, reducing costs, and enabling better patient experiences. Role We're looking for a Staff Data Engineer to architect and build our EHR integration layer from the ground up. This is a foundational role where you'll establish the initial dbt project structure, data models, and transformation patterns that will power how we integrate and standardize Electronic Health Record data across diverse healthcare systems. You'll join a dynamic, cross-functional team at the heart of our product strategy, with the unique opportunity to make architectural decisions that will shape our EHR data platform for years to come. This greenfield project gives you the freedom to design scalable, resilient data infrastructure leveraging AWS, Temporal, dbt, Snowflake and Postgres from day one. Your work will establish the foundation for next-generation AI solutions built on clean, standardized healthcare data. What You'll Do - Architect the initial dbt project structure and establish modeling patterns for our EHR integration layer. - Design and build foundational data models that normalize and standardize data from diverse EHR systems (Epic, Cerner, NextGen, etc.). - Establish data quality frameworks, testing strategies, and observability patterns for the EHR integration layer. - Create reusable transformation patterns and documentation that enable rapid integration of new EHR data sources. - Collaborate with product and engineering teams to define data contracts and specifications for the EHR layer. - Build resilient data pipelines that handle the complexities of healthcare data (HL7, FHIR, proprietary formats). What You Bring - 5+ years of data engineering development experience with a focus on cloud-based data pipelines and infrastructure. - Strong experience architecting greenfield data platforms and establishing foundational patterns. - Expertise with dbt, including project architecture, macros, testing strategies, and documentation. - Deep expertise in SQL and data modeling (dimensional modeling, normalization strategies). - Experience with healthcare data standards (HL7, FHIR, X12) is a strong plus. - Expertise in relational and columnar databases (Snowflake, Postgres). - Experience with data orchestration tools (Airflow, Dagster, Temporal, etc). - Excellent communication and documentation skills - you'll be establishing patterns others will follow. - Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent experience. Nice To Haves - Experience at a scale-up, or rapid growth, technology company - Experience working in the healthcare industry involving billing/claims data - Experience with Snowflake - Experience with Terraform or OpenTofu - Experience with monitoring tools (HyperDX) Our Tech Stack - Databases: Snowflake (primary), Postgres - Cloud Infrastructure: AWS (S3), Temporal - Languages: SQL, Python, dbt Required Technical Exercise - submissions without this component will not be considered: - Please spend no more than 20 minutes completing a quick coding exercise by following the instructions here. California Salary Range $230,000—$280,000 USD

About Us Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence. We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions —so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we’re tackling big challenges in an industry that’s ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data that can support automation, prioritization, and decision workflows—and it’s why we are leading the way. Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. Ready to make an impact? Join us and let's build the future together. About the Role Our Data Distribution Engineering team is looking to bring on a Data Engineering Intern to be part of our fast-growing team. We see massive growth in our future and would love for you to be a part of it! You will partner with customers and several internal teams and extract data from the industry leading data platform which is built on highly scalable, flexible and resilient cloud architectures. As a trusted customer advocate, you will have the opportunity to guide a client’s successful adoption of Abacus’s core data management offerings. Your day to day: - Work with clients and implementation teams to understand the data distribution requirements. - Perform data analysis and data mapping required to produce client output. - Build the data distribution extracts and scripts. - Optimize the performance of the data extract scripts. - Foster a dynamic, high-preforming, and collaborative culture. - Guide team members to solve issues and help them to understand any challenges. - Spearhead clients’ projects and handle client calls. - Constantly think about process enhancements and bring different ideas into table. What you bring to the team: - 2+ years of experience working with healthcare data. - Understanding and passion for healthcare data and systems – knowledge on Membership, Claims, Provider and other domains. - Strong experience writing queries, performing data analysis, data profiling and reporting. - Performance optimization experience with understanding of how to fine tune the queries. - Experience handling a large volume of data. - Ability to communicate with technical and non-technical stakeholders. - Ability to seek better analytical solutions to abstract business problems. - Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. - Experience, coupled with a willingness, to learn new things - Desire to contribute individually, with the ability both to self-direct work and to collaborate with others. - Strong SQL Programming skills. - Strong project management and organizational skills. What we would like to see, but not required: - Experience working with an AWS, Azure, Databricks, Spark. - Experience working with Snowflake. - Understanding or experience working for a cloud-based data services provider to large healthcare clients. Compensation: Compensation for this role is $30/hour or $62,400 per annum. What you’ll get in return: - Unlimited paid time off – recharge when you need it - Work from anywhere – flexibility to fit your life - Comprehensive health coverage – multiple plan options to choose from - Growth-focused environment – your development matters here #LI-RF1 #LI-Remote Our Commitment as an Equal Opportunity Employer As a mission-led technology company helping to drive better healthcare outcomes, Abacus Insights believes that the best innovation and value we can bring to our customers comes from diverse ideas, thoughts, experiences, and perspectives. Therefore, we dedicate resources to building diverse teams and providing equal employment opportunities to all applicants. Abacus prohibits discrimination and harassment regarding race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. At the heart of who we are is a commitment to continuously and intentionally building an inclusive culture—one that empowers every team member across the globe to do their best work and bring their authentic selves. We carry that same commitment into our hiring process, aiming to create an interview experience where you feel comfortable and confident showcasing your strengths. If there’s anything we can do to support that—big or small—please let us know.

Industry Insight Transportation logistics is the foundational industry that powers everything we rely on daily, yet it remains a complex and fragmented domain ripe for technological revolution. The US transportation logistics industry alone is an $800 billion market. Alvys is not just participating in this change; we are driving it as the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to truly transform this essential sector. Your role will be at the forefront of automating and standardizing a sector that moves trillions of dollars' worth of goods annually, predominantly by truck, but still lacks modern tools and solutions. Your leadership will help bridge this gap, bringing innovative technologies to a traditionally underserved and mission-critical industry. About Alvys Alvys is the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to dominate and truly revolutionize the $800 billion US transportation logistics industry. We're not just iterating on old tools; we're building a world-class, multi-tenant SaaS platform from the ground up to automate, standardize, and transform this essential sector. Join us to apply your technical vision to one of the economy's most mission-critical and underserved markets, making a massive, tangible impact on the movement of global goods. This is where industry experience meets cutting-edge technology to create the undisputed market winner, and you will be a core part of that journey. About the Role As a Staff Data Engineer, you will be the primary architect of our data ecosystem. Alvys is shifting toward a Snowflake-centric data architecture to power our next generation of logistics intelligence. You aren't just building pipelines; you are defining our LLM-based data strategy, enabling large-scale ML model deployment, and leveraging Snowflake Cortex to turn fragmented logistics data into actionable AI-driven products. This is a high-visibility, 'player-coach' position. You will work closely with leadership to ensure our data infrastructure supports real-time operational needs today while scaling for the AI-first logistics world of 2026 and beyond. Our Tech Stack - Data Platform: Snowflake (Warehouse, Cortex AI/ML, Semantic Models, LLM Agents) - Data Pipelines: dbt, Fivetran, Reverse ETL (Census) - AI/ML: Snowflake Cortex, OpenAI, Azure Cognitive - Backend/Infra: .NET/C#, Python, Azure Ecosystem, GitHub Actions Key Responsibilities - Define and implement the strategy for LLM-based data products, including data preparation, semantic layer design, and embedding pipelines for RAG-based applications. - Own the design and evolution of our Snowflake architecture. Lead the implementation of Snowflake Cortex for AI/ML workloads, including semantic models and LLM agents. - Design and maintain reliable, performant ELT/Reverse ETL pipelines. Ensure our multi-tenant SaaS data remains isolated, secure, and performant at scale. - Build and operationalize pipelines for large-scale ML and LLM model development, moving from POC to production-grade deployment within the Snowflake perimeter. - Think holistically about the data estate. Reduce complexity through modularity and well-defined service boundaries (e.g., Medallion Architecture). - Serve as the go-to expert for emerging data trends. Mentor engineers and partner with Product and Design to translate complex business logic into automated deliverables. The Experience You Have - 7+ years of experience in Data Engineering with a proven track record of delivering mission-critical data platforms. - Deep proficiency in Snowflake (Data Modeling, Query Optimization, Security, and Cortex AI functions). - Expert-level skill in SQL and Python. Extensive experience with dbt and modern orchestration (Airflow/Dagster). - Demonstrated experience building pipelines for ML or LLM-based applications, including feature engineering and model deployment. - Competency in Azure (preferred) or other major cloud providers, including CI/CD and infrastructure-as-code principles. - Experience driving cross-team consensus on architectural decisions and mentoring junior/mid-level engineers. The Way You Work - Ownership: You take end-to-end responsibility. If it’s in production, it’s yours—from the initial schema design to the final dashboard latency. - Pragmatism: You believe technical debt is a strategic choice. You choose solutions that scale and solve real problems over theoretical "perfection." - Simplicity: You prioritize modularity and clean design to reduce cognitive load in a complex logistics domain. - Transparency: You democratize data. You ensure insights are accessible across the organization and participate in constructive feedback loops. Equal Employment Opportunity Alvys is an equal opportunity employer and as such, we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable laws. We are dedicated to growing a diverse team of highly talented people. We’re dedicated to building a workplace where we give each other the strategies, support, and space we each need to thrive—believing in and bringing out the best of everyone. If you require any accommodations during the recruitment process, whether it be alternate forms of material, accessible meeting rooms, etc., please let us know and we will work with you to meet your needs. For information about Alvys's privacy practices, see our Privacy Policy.

• Design, implement, and maintain Infrastructure-as-Code (Terraform) for the Data Platform and supporting infrastructure. • Own infrastructure lifecycle management across environments (dev/stage/prod). • Ensure availability, scalability, and fault tolerance of platform components. • Improve environment isolation and infrastructure standardization. • Monitor and optimize infrastructure cost and resource utilization. • Design and maintain CI/CD pipelines in GitLab for infrastructure and platform components. • Implement automated testing, validation, and policy enforcement for infrastructure changes. • Establish and evolve logging, monitoring, alerting, and tracing standards. • Lead migration of legacy infrastructure to standardized, modernized architecture patterns. • Collaborate with cross-functional technical teams to ensure reliable and scalable infrastructure for data workloads.