• Build the knowledge layer that sits underneath Superads' AI agents — the systems that give them genuine understanding of a brand rather than just access to its documents. • Design how brand knowledge is represented, stored, and continuously updated: the structures that let an agent reason about a brand the way a senior strategist would, not just retrieve what's been written down. • Develop agentic search capabilities — systems that let agents reason about what they don't know, identify knowledge gaps, and navigate information dynamically rather than relying on fixed retrieval pipelines. • Evaluate and iterate on architectures for knowledge retrieval and reasoning, identifying where current approaches break down and driving more interesting solutions. • Translate emerging AI research and patterns into production-ready systems that measurably improve output quality and reliability. • Work closely with the product and AI engineering teams to ensure the knowledge layer directly improves what users experience — staying connected to product impact even when the work takes you deep into infrastructure.

• Database Design & Management: Design, build, and maintain databases that power Hologram's operations, with a focus on simplicity, reliability, and scalability • Pipeline Development: Build and maintain ETL pipelines that move and transform data reliably, with monitoring and alerts to catch breakages fast • Database Reconstruction & Simplification: Audit existing pipelines and data models, identify complexity, and refactor bad decisions into clean, maintainable solutions — incrementally improving what exists rather than starting from scratch. • Data Modeling & Transformation: Own and evolve our dbt models, ensuring data is clean, well-documented, and usable by people outside of engineering • Analytics & Reporting: Write expert SQL to surface insights across the business — from customer usage trends to operational performance • Business Intelligence: Build and maintain dashboards and reports in Sigma that give internal teams clear visibility into the metrics that matter

• Work with laboratory data sources such as LIMS, ELN, Excel, and SharePoint • Design and build data pipelines using Python and SQL • Transform and structure messy R&D data into clean, well-organized datasets • Process and manage data using Azure and Databricks • Collaborate with cross-functional teams, including scientists and analysts • Ensure data quality, consistency, and usability across systems

About Dimagi Dimagi is an award-winning social enterprise and a certified B-corp and Benefit Corporation. We build software solutions and provide technology consulting services to improve the quality of essential services for underserved populations. Our open-source technology platform, CommCare, is the world’s most widely-used and researched mobile data collection platform for frontline workers. Our choice to be a certified B-Corp and to legally incorporate as a Benefit Corporation sends a clear signal to our partners, our team members, and our communities that we not only believe but also take action in using business as a force for good. This approach combines our passion and commitment to tackle complex health and social inequities and work towards a brighter future for all. About the Position Dimagi is looking for a Data Engineer II to join our US Solutions Division. This position will be affiliated with our Cambridge, MA office but is open to remote employment within the United States. This is a 12-month fixed-term position with the possibility of renewal based on business requirements and mutual interest. The Data Engineer II will be part of Dimagi’s US Solutions Division Data & Analytics team, a group of engineers and data specialists responsible for building, maintaining, and evolving Dimagi’s Data Platform in support of current and future project work. The primary technologies used by the current data platform are Snowflake, Tableau, and various AWS cloud tools. In this role, you will contribute hands-on to the design, implementation, and operation of data pipelines, warehouse transformations, data visualizations, and supporting infrastructure, while working closely with technical leadership to ensure platform reliability, scalability, and alignment with business needs. The data systems you help build and maintain will directly support public health and human services programs, enabling frontline teams and government partners to deliver care and services more effectively. This position is well suited for someone who enjoys hands-on technical work in a small, collaborative environment. As a member of a lean team, you will be expected to work across functional areas, adapt quickly to new problem spaces, and contribute meaningfully to data systems that support real-world service delivery and decision-making. This role assumes comfort using AI-assisted tools to support analysis, documentation, troubleshooting, and learning in a complex technical environment. Responsibilities - Contribute to the technical integrity and evolution of the Data Platform tech stack, working closely with other Data Engineers, the Director of Technology, and the USS Tech Lead. - Design and implement core features and enhancements within the Data Platform, including contributing to technical specifications, conducting targeted technical research, and translating requirements into production-ready solutions. - Responsible for executing and maintaining DevOps workflows supporting the Data Platform, including performance monitoring, platform upgrades, deployment frameworks, and operational improvements, with guidance and mentorship from more senior Data Engineers as needed. - Use AI-assisted tools thoughtfully to accelerate development, debugging, documentation, and operational analysis, while understanding and validating outputs to ensure correctness, reliability, and security. - Build and maintain robust data extraction, loading, and transformation processes for both Dimagi managed (i.e. CommCare) and external data sources, enabling efficient, reliable data pipelines and their long-term development and operation using both SQL and Python scripting. - Design and develop data warehouse transformations, using SQL-based approaches and supplementary tools such as dbt. - Collaborate with internal teams and external partners on the design and implementation of enterprise data architectures based on industry standards and partner specific analytics needs. - Conduct ad hoc analyses and support the development of business intelligence outputs, including dashboards and visualizations using Tableau and other tools. The ideal candidate will have some or all of the following experience: - 2–5 years of experience in data engineering or a similar technical role, with a proven track record of designing and evolving scalable data systems. - Experience building maintainable, long-term technical solutions using software development best practices (version control, testing, and iterative development). - Hands-on expertise in building and managing production-grade pipelines using ETL/ELT tools (e.g., dbt, Airflow, Prefect, Fivetran, or Talend). - Strong proficiency with cloud-based data platforms (AWS, Snowflake, etc.) and a diverse range of data ingestion, processing, and storage technologies. - Expert-level SQL for complex data engineering and analysis, paired with proficiency in Python and associated data-oriented toolkits. - A deep understanding of dimensional modeling concepts ((e.g. OLAP cubes, star schemas, kimball architecture vs. alternatives like inmon) - Proven ability to partner with technical stakeholders to clarify requirements and deliver effective, end-to-end data solutions. - Proficiency in using AI-assisted tools for code generation, debugging, and optimization, with the ability to rapidly adapt to new schemas and tools in a fast-paced environment. - Comfortable working "in the trenches" of production systems to test, iterate, and optimize operational workflows. - Eligible to work in the United States Bonus Experience - Experience in enterprise data architecture, service-oriented frameworks, data integration and harmonization, data strategy and governance, high-performing data lakes, data operations and delivery and data ingestion frameworks supporting batch/real-time - Experience writing and maintaining production ready code in a high level programming language (Python, Java, C++ etc.) - Experience with data analysis software (Jupyter Notebooks, R, etc.) and data visualization tools (Tableau, Power BI, Superset, etc.). - Healthcare experience: either in healthcare data or public health data collection methodologies and workflows - Experience and comfort working independently with partners for requirements gathering and solution development in an agile software development environment, using JIRA and Asana to manage tasks between technical and client-facing teams Benefits and Compensation We aim to make a difference, not just as a company but also as an employer! We are transparent about salaries at all levels of the organization and have a standard, global pay scale for all positions. Our salaries are cost of living adjusted and non-negotiable. The estimated salary range for this position is 82,810 USD - 130,319 USD annually. Your final salary within the range will be dependent on where you are geographically based and might fall outside of this estimated range. However, the benefits we offer are geared towards having a strong impact on our staff’s well-being. A few of our key benefits are outlined below: - 100% employer-sponsored medical insurance paired with a generous Health Reimbursement Account (HRA) fund - Access to voluntary dental and vision insurance plans - A 401K plan with up to a 4% employer match - Employee stock option plan - 30 days paid time off inclusive of holidays - Unlimited sick time and excellent parental leave policy - Access to a flex-time policy that allows employees to work based on a flexible work schedule - Access to an Employee Assistance Program (EAP) through ComPsych Dimagi is an Equal Opportunity Employer. We celebrate and support diversity and are committed to providing a work environment that is inclusive and free of discrimination and harassment. All employment decisions are based on individual qualifications without regard to race, color, religion, age, sex, sexual orientation, ethnicity, gender identity and expression, national origin, family or parental status, veteran or disability status.