Jobs at Sedona Digital

Lead client-facing AI transformation engagements from opportunity discovery through proof-of-concept adoption. Gather requirements, identify high-ROI use cases, build business cases and roadmaps, manage AI pipelines, and collaborate with engineering teams on prototypes using client data and LLM services. Secure executive buy-in, promote responsible AI governance, and transition successful solutions to production delivery teams.

Designs, implements, administers, and optimizes Microsoft 365 modern workplace environments. Responsibilities include managing Teams, SharePoint, OneDrive, Exchange Online, Azure AD, Intune, Conditional Access, Power Platform, licensing, security, compliance, identity, endpoint management, and user support. The role also involves troubleshooting, onboarding and offboarding, documentation, customer workshops, knowledge transfer, incident management, governance, adoption initiatives, mentoring junior engineers, and serving as an M365 technical escalation point.

Supports accounting, month-end and year-end close, financial reporting, budgeting, forecasting, reconciliations, consolidation, and financial analysis. The role also improves ERP and finance systems, develops Power BI reporting solutions, maintains controls and procedures, and contributes to automation and process efficiency across an international, multi-entity business.

Owns business and commercial operations across IT services engagements, overseeing revenue, margin, utilisation, forecasting, delivery health, renewals, governance, and reporting. Partners with Finance, Sales, delivery, and leadership to identify risks, drive corrective actions, improve processes, and maintain operational discipline. Leads service-improvement initiatives, manages systems and data quality, and coaches a Business Operations Analyst.

Designs, builds, and maintains scalable AWS and Snowflake data platforms, pipelines, integrations, data models, and quality controls. Owns production workflows, including SAS-based healthcare claims processing, while improving monitoring, resilience, security, governance, performance, and cost efficiency. Collaborates with clients to deliver analytics and AI-ready datasets, modernize legacy processes, document solutions, and support reliable data operations.

The role involves managing multiple business change projects, coordinating stakeholders, leading business analysis, and ensuring project success across various departments.

Develop and deploy machine learning and statistical models that solve business problems and create measurable impact. Responsibilities include exploratory data analysis, feature engineering, experimentation, model optimization, explainability, MLOps, prompt engineering, and cloud-based data collaboration. The role involves working with clients and stakeholders, communicating insights through visualization and storytelling, and contributing to scalable analytics, Generative AI, and data science solutions.

Lead enterprise-scale data science and AI initiatives, defining lifecycle best practices, architecture, governance, metadata frameworks, and MLOps practices. Design and deploy machine learning, statistical, optimization, and LLM solutions using cloud platforms. Lead multidisciplinary teams, translate business needs into analytical solutions, collaborate with engineers and stakeholders, and communicate insights to technical and executive audiences.

Lead improvement of operational processes, manage intake/workflows and BAU activities, ensure data quality in Dynamics 365 Business Central, support UAT and system enhancements, produce reporting and dashboards, coordinate cross-functional stakeholders, and document scalable SOPs and process changes.

Design, implement and improve cloud platform services and CI/CD pipelines; automate operations; mentor juniors; support Windows, Linux and Kubernetes environments; collaborate on security remediation and provide platform expertise (GitLab, Docker, AWS, Terraform, Istio, Kafka, ELK).

Design and implement scalable Azure data platforms, develop data pipelines, and support clients with data modernization and governance practices.

Lead technical recruiting for software, data engineering and DevOps roles: source and engage candidates, screen and interview, manage pipelines, collaborate with hiring managers, support offers and onboarding, and maintain ATS reporting and recruitment metrics.

Conduct 60-minute technical interviews for senior data engineering candidates, evaluate cloud-based data platform architecture, ETL/ELT pipelines, distributed processing, security, data modelling, and communication. Complete scorecards, provide hiring recommendations, and collaborate with recruiters to improve assessments.

Lead and scale a global technology-focused talent acquisition function, managing a team of recruiters while strategizing recruitment across various regions.