• Design and manage Feed the Children’s modern cloud data infrastructure, with ownership of Microsoft Fabric and Azure. • Lead the stand up and evolution of Feed the Children’s Fabric platform and serve as its primary Product Owner. • Collaborate closely with ERP and CRM teams, and coordinate with Data Governance leadership. • Ensure seamless integration of data and data flows from various sources, including ERP systems, CRM systems, DHIS2, external datasets and APIs, and other business applications. • Implement processes and tools to ensure high data quality and consistency across the organization.

• Building a modern, scalable enterprise data platform that supports analytics, business intelligence, and AI. • Creating trusted, governed data products that become the foundation for enterprise reporting and decision-making. • Designing reliable, automated data pipelines that integrate our core business systems into a single, scalable architecture. • Establishing engineering standards for data quality, governance, security, observability, and platform reliability. • Partnering with business and technology leaders to solve complex data challenges and enable new capabilities across the organization. • Helping define the long-term vision and technical direction of Sangoma's enterprise data platform.

• Implement ingestion pipelines and Airflow DAGs from a senior engineer's design, using the team's scaffolding and conventions — including writing the code, unit tests, and documentation • Support data security and governance work, such as PII masking and access controls, following established patterns • Contribute to data delivery work, including reverse ETL integrations, under guidance from senior engineers • Add and extend fields in existing pipelines, incorporating review feedback and applying learned patterns on future work • Take oncall pages for pipeline failures, work through runbooks, and escalate with clear context when needed • Pair with senior engineers on data integrity issues you can't yet diagnose alone • Write clear, reviewer-friendly PR descriptions and ask clarifying questions before starting new work • Flag blockers early and with context rather than going quiet when stuck • Build strong working relationships with internal stakeholders (BI analysts, other data engineers, data scientists) and help gather and clarify requirements • Conduct and participate in code and system inspections • Help the team define and adhere to data engineering best practices • Mentor more junior data engineers as you grow into the role

• Focus on engineering, building, and maintaining data pipelines, applications, workflows, and governance capabilities inside the Palantir platform, particularly Code Repositories, Workshop, Slate, and AIP. • Build and configure data pipelines using Code Repositories and Pipeline Builder. • Build applications and workflows using Workshop and Slate within Palantir. • Develop data pipelines involving collecting, transforming, cleaning, and validating data, using Palantir. • Develop and maintain governance applications that monitor platform performance, compliance, and operational health. • Implement and maintain platform‑driven automations and monitoring capabilities. • Coordinate with non-technical users to gather requirements. • Identify, summarize, and catalog data fidelity issues, and make recommendations to the client on how to resolve or mitigate the issues. • Apply industrial engineering methods (time studies, process mapping, Lean/Six Sigma, constraints analysis) to improve depot and sustainment processes. • Conduct capacity, throughput, and bottleneck analyses for depot maintenance, MRO, supply chain, and production environments to inform investment, resourcing, and modernization decisions. • Integrate data from ERP/MRO/maintenance systems into simulation models to generate actionable insights for forecasting, scheduling, and scenario analysis. • Collaborate with cross‑functional stakeholders (operations, supply chain, engineering, analytics) to design and test “what‑if” scenarios that support strategic planning and infrastructure decisions. • Prepare and deliver clear decision‑support briefings, visualizations, and recommendations for senior leaders regarding depot performance and modernization impacts. • Support adoption of advanced analytics and digital engineering approaches (e.g., predictive modeling, digital twins) to improve depot efficiency and readiness outcomes. • Develop trusted relationships with clients at all levels of the organization to obtain a more complete perspective and understanding of our clients’ mission, challenges, and goals to deliver tailored solutions. • Support business development efforts (e.g., responding to RFPs/RFIs, developing white papers, creating pitch decks and capability briefings, etc.).