• Design, develop, and maintain secure, scalable ETL/ELT pipelines processing structured and unstructured data from multiple sources • Build and optimize data models and processing workflows to support BI, analytics, and reporting needs • Develop monitoring and alerting solutions to ensure pipeline performance and data quality • Build insightful dashboards, reports, and datasets in Domo • Integrate data from external APIs and third-party systems (e.g., Salesforce) • Collaborate with Software Engineering, Architecture, Product, Analytics, and IT teams • Translate business requirements into robust technical solutions • Conduct code reviews and provide feedback to engineering team members • Mentor other data engineers and contribute to onboarding efforts • Participate in Agile ceremonies including standups, retrospectives, and planning

• Design and develop technical specifications for an interoperability middleware based on client's SMART Guidelines. • Support subject matter experts in defining and validating data dictionary mappings. • Design mapping logic between surveillance systems such as DHIS2, SORMAS, Go.Data, OpenELIS, and other health information systems. • Identify interoperability gaps and propose scalable technical solutions. • Document architecture decisions, interoperability workflows, and design trade-offs. • Develop specification frameworks aligned with client's SMART Guidelines, ICD-11, LOINC, SNOMED CT, and other healthcare interoperability standards. • Contribute to the design of AI agent frameworks and orchestration layers supporting data integration. • Configure and optimize relational and graph/network database environments. • Develop scalable ingestion frameworks capable of operating in both cloud and on-premises environments. • Implement staging layers for data ingestion, validation, transformation, harmonization, and quality assurance. • Design synchronization mechanisms supporting low-resource environments and offline data collection. • Develop production-grade ETL/ELT pipelines to automate ingestion and processing of surveillance datasets. • Build AI-assisted workflows and agent-driven mechanisms for extracting and integrating data from systems such as DHIS2, SORMAS, EWARS, and other external sources. • Implement automated processes for data validation, cleansing, deduplication, normalization, and harmonization. • Ensure pipelines efficiently process heterogeneous datasets while delivering high-quality data for analytics and modelling teams. • Optimize pipeline performance, scalability, and reliability. • Develop automated workflows for weekly and monthly surveillance reports and situation reports (SitReps). • Build APIs and data export services supporting downstream analytics and modelling. • Develop clean analytical datasets optimized for threshold analysis and collaborative modelling. • Support dashboard development and data visualization initiatives. • Ensure reporting infrastructure meets security, performance, and interoperability requirements.

Role Description We are looking for a detail-oriented and organized Data-Focused Project Coordinator to support the planning, execution, and completion of key projects. This role requires proficiency in Business Intelligence tools , strong data management skills, and the ability to work effectively in a fast-paced environment. - Support project management tasks, ensuring timely delivery. - Use Business Intelligence tools to analyze and visualize data for actionable insights. - Maintain accurate project documentation and validate data accuracy. - Collaborate with teams to create detailed reports and support decision-making. Qualifications - Proficiency in Business Intelligence tools - Strong attention to detail, organizational, and analytical skills. - A basic understanding of database systems and validation processes is a plus. - Experience using and improving AI-driven workflows is highly valued. - Proficiency in Russian and/or Ukrainian languages. Company Description INFUSE is a demand generation company providing solutions to B2B organizations. We help clients and partners to deliver audience, buyers, and account engagement that meets their goals. With a global team operating across more than 60 countries, the company has been recognized multiple times on the prestigious Inc. 5000 list, and has received over 60 other industry awards, including Inc. Best Workplaces.

Role Description The Data Engineering & AI/ML capability serves as the backbone of our organization's data-driven operations. We are seeking a talented and motivated Data Engineer to join our dynamic Data Engineering & Analytics team. As a key member of our engineering team, you will play a crucial role in: - Constructing and optimizing data pipelines - Implementing efficient storage solutions - Orchestrating the infrastructure necessary to support our customer’s data-driven initiatives Location: Primarily Remote. Candidates must be based in CA or DC Metro Area for proximity to project and client teams. Security Clearance Requirement: Applicants must be US citizens and eligible to obtain and maintain an active Secret security clearance or above. Qualifications - Solid understanding and experience with SQL and relational database concepts - Solid understanding of database technologies, data warehouses, and ETL tools (e.g., MySQL, PostgreSQL, Beam, Airflow, and Kafka) - Experience with data analysis tools (e.g., Jupyter, Colab, Pandas) - Experience with data visualization tools (e.g., Tableau, Looker, PowerBI, Qlik, and SuperSet) - Previous experience developing data strategies and facilitating data migrations into production systems - Experience with cloud platforms (e.g., AWS, Azure, GCP) - Proficiency in programming languages such as Python, Java, or C++ - Strong software engineering skills with an emphasis on writing clean, modular, and maintainable code - Familiarity with version control systems (e.g., Git) and collaborative development workflows - Excellent problem-solving and critical-thinking skills - Effective communication skills and ability to work in a collaborative team environment Requirements - Experience with other database technologies (e.g., NoSQL, Graph) - Any of the below cloud certifications: - Google Cloud Professional Cloud Architect - Google Cloud Professional Database Engineer certification - Google Cloud Professional Data Engineer - Experience with additional data processing tools and technologies (e.g., Spark, Hadoop) - Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) Benefits - Salary Range: $102,850 - $170,000