Jobs at Cognite

Develop and deploy data science and machine learning solutions for industrial customers across energy, manufacturing, pharma, and utilities. Responsibilities include facilitating discovery workshops, cleansing and analyzing data, implementing Python-based physical and machine learning models, applying generative AI, building Cognite Data Fusion web applications, and collaborating with data engineers, project managers, and solution architects on customer deliveries.

Lead scalable data engineering solutions using Cognite Data Fusion, including integrations, extraction, data modeling, cleansing, analysis, and production-grade pipelines. Collaborate with data scientists, architects, project managers, engineering, product teams, customers, and partners. Conduct code reviews, apply DevOps and CI/CD practices, support Cognite tools and SDKs, and translate customer needs into product offerings.

Design and implement data infrastructure, custom extractors, ETL pipelines, data models, and visualization prototypes for industrial clients. Collaborate with solution architects, subject matter experts, product teams, and stakeholders to deliver reliable data solutions using Python, Spark, SQL, Kafka, REST APIs, and Docker. The role requires experience in oil and gas or manufacturing, client-facing communication, and onsite travel from a hybrid Houston location.

Designs and scales technical learning content and experiences for Cognite Academy. Translates complex technology concepts into learning materials, labs, assessments, and hands-on experiences. Owns the Skilljar platform, including publishing, learning paths, reporting, configurations, and automation. Partners with technical and product teams, applies AI-enabled content tools, analyzes learner data, and continuously improves enterprise education programs, certifications, and learning outcomes.

Own and optimize Cognite’s talent technology stack, including Greenhouse, Claude, HiBob, and SkillJar. Configure recruiting workflows, automations, integrations, reporting, performance and workforce planning processes, and AI-enabled employee development tools. Serve as the internal subject-matter expert, maintain documentation and training, manage vendors, and improve system adoption and data integrity. This is a senior individual-contributor role with manager-level scope but no direct reports.

Designs and governs complex enterprise SaaS deals for Cognite’s global revenue organization. Advises sales leaders on pricing, contract structures, margin protection, negotiation, and approval workflows. Coordinates Legal, Finance, Product, and executives while developing CPQ templates, GenAI proposal reviews, discounting guardrails, Salesforce data processes, commercial playbooks, and enablement programs.

Lead data science solutions for industrial customers across oil and gas, manufacturing, and power and utilities. Responsibilities include workshops, data cleansing, exploratory analysis, machine learning model development in Python, model deployment, generative AI applications, web application development on Cognite Data Fusion, and customer collaboration. The role also contributes to reusable solution templates, supports customer data science work, and mentors internal colleagues.

Owns the architecture, development, and operation of security-critical backend systems for authentication, authorization, identity, and audit. Designs scalable gRPC and HTTP APIs and Kubernetes-based microservices, drives threat modeling, performance tuning, and reliability engineering, and mentors engineers. Requires strong Kotlin expertise, distributed systems experience, modern authentication and authorization knowledge, and hands-on cloud-native experience with Elasticsearch and major cloud platforms.

Design and implement scalable data engineering solutions using Cognite Data Fusion. Build integrations, data pipelines, extractions, models, and analyses with Python, SQL, Java, and REST APIs. Collaborate with data scientists, architects, project managers, customers, and partners to deliver industrial data solutions. Conduct code reviews, apply DevOps and quality practices, support customer engineering tasks, contribute to SDKs and tools, and help prioritize product improvements.

Design and implement production-grade data infrastructure, pipelines, integrations, data models, and cleansing solutions using Cognite tools, SQL, Python or Java, and REST APIs. Collaborate with architects, subject matter experts, product teams, customers, and partners to deliver data-driven solutions. Optimize security, monitoring, logging, access control, and disaster recovery while mentoring and recruiting junior data engineers.

Build and operate Cognite’s serverless execution engine and workflow orchestration platform. Responsibilities include designing scalable multi-tenant backend services, APIs, scheduling and retry systems, observability, CI/CD, automated testing, performance optimization, incident response, and reliability engineering. The role also supports ML workloads, contextualization pipelines, and potentially vector infrastructure across cloud environments.

Lead scalable data engineering solutions using Cognite Data Fusion, including integrations, data extraction, modeling, cleansing, pipelines, and analysis. Collaborate with data scientists, architects, project managers, customers, and partners to deliver industrial data solutions. Conduct code reviews, apply DevOps and engineering best practices, contribute to Cognite tools and SDKs, and help prioritize product offerings based on customer needs.

Designs complex end-to-end solutions combining Cognite SaaS products with customer ecosystems. Leads technical discovery, data modeling, integrations, cloud architecture, visualization, implementation quality, monitoring, security, and operational support. Advises customers and partners on Cognite Data Fusion while collaborating with sales, delivery, data science, product, and engineering teams. Requires strong Python and software development expertise, cloud and DevOps experience, enterprise integration knowledge, and data architecture skills.

Drive pipeline growth through outbound prospecting, inbound lead follow-up, qualification meetings, account research, and personalized outreach. Use sales tools to identify decision-makers, engage manufacturing prospects, and transfer qualified opportunities to account executives. Collaborate with sales and marketing, manage event leads, maintain CRM records, gather market insights, and continuously optimize outreach strategies.

Leads product strategy, roadmap, development, and success for Cognite Data Fusion, focusing on usability, time to value, AI integrations, and industrial data solutions. Collaborates with customers, engineers, designers, subject matter experts, and go-to-market teams to define requirements, manage tradeoffs, launch products, and drive adoption. The role also mentors junior colleagues, leads complex global initiatives, and may grow into managing a product management team.

Lead end-to-end solution architecture for industrial customers, designing enterprise architectures, integrations, data models, ingestion pipelines, and user-facing solutions. Advise customers and project teams, collaborate with Sales, Engineering, and Product Management, support delivered solutions, and drive product adoption. The role requires hands-on Python and software development expertise, customer and executive engagement, team coaching, and the ability to work independently across industrial digitalization projects.

Lead end-to-end solution architecture and design for industrial customers, including enterprise architecture, integrations, data models, ingestion pipelines, and user-facing solutions. Partner with customers, sales, engineering, and product teams to deliver successful implementations, support adoption, define product opportunities, and provide technical leadership. The role requires hands-on Python and software development expertise, stakeholder management, coaching, and independent ownership.

Leads technical presales engagements for Cognite’s industrial AI and data solutions in the oil and gas sector. Designs solution architectures, prototypes AI-driven applications, develops integrations, conducts client workshops and demonstrations, supports sales opportunities, translates customer feedback into product requirements, and mentors field engineers. Requires expertise in industrial data, OT/IT convergence, cloud platforms, APIs, data integration, and enterprise client engagement.

Lead end-to-end delivery of complex Industrial AI and digital transformation projects, from kickoff through deployment, adoption, and value realization. Own scope, schedules, budgets, quality, financial performance, risks, governance, and customer outcomes. Collaborate with technical and customer teams, lead stakeholder communications and steering committees, support change management and training, and identify expansion opportunities. Apply PMO methodologies and continuously improve delivery practices.

Lead end-to-end delivery of complex Industrial AI and digital transformation projects, from kickoff through deployment, adoption, and value realization. Own scope, schedules, budgets, quality, financial performance, risks, governance, and customer outcomes. Partner with technical teams and executive stakeholders, manage steering committees, facilitate value realization workshops, support change management and training, and identify expansion opportunities. Apply PMO methodologies and continuous improvement practices across enterprise software and industrial technology implementations.