Jobs at Datatonic

Drive strategic account growth and new-logo acquisition across Media and Entertainment clients. Build executive relationships, diagnose business and technical challenges, develop Google Cloud-backed data and AI transformation roadmaps, lead commercial negotiations, and collaborate with Google Cloud and internal delivery teams to realize client value and expand engagements.

Design and develop scalable data pipelines and cloud infrastructure for analytics, visualization, and machine learning applications. Collaborate with data scientists, ML engineers, and analysts to deliver data solutions using GCP, dbt, and Looker. Optimize ETL and big-data processing, maintain resilient code and infrastructure, troubleshoot systems, and mentor engineers while supporting client-facing projects.

Legal Counsel will manage commercial contracts, including drafting and negotiating MSAs, NDAs, and DPAs; oversee contract repositories, obligations, renewals, and governance; and develop AI-enabled legal workflows and review playbooks. The role also provides advice on employment law, GDPR, compliance, and corporate governance while partnering with sales, finance, and delivery teams. Candidates need solicitor qualification, 3–6 years PQE, commercial technology or professional services contracting experience, contract management expertise, and strong drafting, negotiation, analytical, and communication skills.

Coordinate regional HR operations across the employee lifecycle, including employee relations administration, employment contracts, compliance, payroll, HRIS data, absence management, immigration and relocation, benefits, onboarding, offboarding, and employee support. The role partners with regional People Business Partners and global People Operations teams, maintains accurate records, supports mandatory training and engagement events, and ensures legal compliance across multiple countries.

Lead Datatonic’s global Learning and Development strategy, building Google Cloud, AI, and consulting capabilities across technical and non-technical teams. Commercialize internal training products through the Datatonic Academy, support Google Cloud Authorised Training Partner activities, and drive customer education. Oversee learning pathways, certification programs, hackathons, content, incentives, apprenticeships, graduate schemes, and strategic training initiatives while influencing executives, engineers, sales teams, and enterprise clients.

Lead DevOps pipeline design and implementation, advise clients on DevOps best practices, establish DevOps functions, and engage stakeholders to ensure seamless delivery across projects.

Drive strategic revenue and transform enterprise client relationships through long-term engagements, navigating challenges and delivering measurable business value.

Lead and implement end-to-end ML solutions: translate vague requirements into models, run ML experiments, apply GenAI, design ML architectures on Google Cloud, build production-grade code, handle MLOps, data engineering, optimization, deployment, and client-facing project leadership.

Senior Enterprise Account Executive responsible for building and closing large, outcome-led Data/AI/Cloud deals (£250k+), expanding and networking within Nordic enterprise accounts, conducting frequent on-site discovery, orchestrating internal technical resources, and moving accounts from tactical conversations to strategic, transformational programs while preparing for a leadership transition.

As a Machine Learning Engineer, you will develop ML models, optimize solutions, automate workflows, and design ML architecture while ensuring high-quality production software delivery.

The Account Executive will drive sales, develop strategies for business growth, manage accounts, and lead collaborations with clients and teams in the insurance sector.

Lead pre-sales activities at Datatonic, shaping data and AI solutions, architecting transformations, and advising clients across various industries. Build trust with C-suite, manage RFPs, and represent the company in strategic engagements.

Lead and expand Datatonic's Google Cloud partnerships across the Nordics by developing JBPs and GTM plans, driving partner-sourced pipeline and co-sell motions, coordinating with sales and partner engineers, managing partner operations, QBRs, onboarding, and executing joint solution development to meet pipeline and sales targets.

As an Experienced Software Engineer, you'll design, develop, and deploy AI applications, ensure performance and scalability, and collaborate with cross-functional teams to deliver production-grade software solutions.

As a Senior Machine Learning Engineer, you will design and implement AI solutions, optimize ML models, and lead projects while engaging with clients to meet business needs.

The Senior Machine Learning Engineer will develop models, lead projects, optimize solutions, and ensure data flow, leveraging AI on Google Cloud.

Manage Google Cloud partner portal administration, deal registration, co-sell tracking, partner onboarding, stakeholder communications, funding utilization, financial reconciliation, tier and scorecard compliance, dashboards, incentive forecasting, and joint marketing campaign reporting. The role coordinates closely with sales, marketing, finance, engineering, Datatonic leadership, Google Cloud representatives, and external partners.

Own and improve security operations for cloud-first infrastructure: tune SIEM detections, improve DLP/CASB/EDR controls, run incident response, automate workflows, and maintain ISO 27001 compliance and evidence.

Manage and grow strategic partnerships across US & Canada for a Google Cloud-focused AI and data consultancy. Drive co-sell initiatives, GTM planning, partner enablement, joint marketing, event execution, partner onboarding, and pipeline generation while tracking partner performance and reporting impact.

Lead architecture and delivery of enterprise-scale data and AI projects on Google Cloud. Provide pre- and post-sales technical advice, design and migrate cloud solutions, mentor architects, collaborate with partners and sales, define best practices, and build next-generation ML products and scalable production-grade platforms.