Who we are: Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks. Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector. Visit gomotive.com to learn more. About the Role: As a Data Engineer on our BI team, you’ll be a key player in Motive’s growth, delivering the data infrastructure for the AI era. You’ll act as the essential link between complex data and key business domains, delivering the high-quality datasets and semantic models that drive global strategy. This is an exciting opportunity to implement cutting-edge tooling, leverage AI to enhance your workflow, and master a modern data stack in a fast-evolving environment. This is the perfect role for a "jack of all trades" data practitioner. You’ll design data models, build robust pipelines, manage DevOps and automated systems, and implement AI-driven data tooling. You’ll even get your hands dirty building dashboards and performing deep-dive analysis. If you love working full-stack and owning the entire data lifecycle, you’ll love this role. What You'll Do: - Collaborate & Strategize: Partner closely with business stakeholders to understand their challenges and design end-to-end architecture that solves complex business problems. - Build & Maintain Data Models: Design, develop, and own robust, efficient, and scalable data models in Snowflake and Iceberg using dbt and advanced SQL. - Orchestrate & Automate: Build and manage reliable data pipelines and CI/CD workflows using tools like Airflow, Python, and Terraform to ensure data is fresh, trustworthy, and infrastructure is version-controlled. - Champion Data Quality: Implement rigorous testing, documentation, and data governance practices to maintain a single source of truth. - Enable Analytics & Workflows: Act as the Product Owner and Tech Lead for your data domains, taking responsibility for the end-to-end data product delivery– from raw ingestion to data models enabling analytics and data apps in tools like Tableau and Retool. - Innovate with AI: Help us build our next-generation data infrastructure by integrating AI capabilities (like Snowflake Cortex AI) to democratize analytics and empower the business. - Architect Observability: Implement monitoring and alerting frameworks (e.g., dbt packages or Monte Carlo monitors) to proactively catch "silent" data failures before stakeholders do. What We're Looking For: - 6+ years of experience in Analytics Engineering, Data Engineering, or a similar role. - Deep expertise in SQL and developing complex data models for analytical purposes (e.g., dimensional modeling). - Hands-on experience with: - Data Warehousing: High proficiency in Snowflake (preferred) and experience with Open Table Formats like Iceberg. - Data Transformation: dbt - Orchestration & ETL: Airflow, Fivetran, Airbyte - Cloud Platform: AWS - Programming/Ingestion: Python - Infrastructure as Code: Terraform - AI-Augmented Development: Proficiency using AI coding assistants (Cursor, Copilot, or Claude) to accelerate development and automate routine tasks. - A strong analytical mindset with a proven ability to solve ambiguous business problems with data. - Excellent communication skills and experience working cross-functionally. - Self-starter with the ability to self-project manage work - A user focus with the ability to understand how a data consumer will use the data products you build Bonus Points (Nice-to-Haves) - Experience building semantic models for natural language querying - Direct experience with advanced Snowflake features (e.g., Snowpark, Cortex AI). - Experience building visualizations and dashboards in tools like Tableau, Retool, or Thoughtspot. Pay Transparency Your compensation may be based on several factors, including education, work experience, and certifications. For certain roles, total compensation may include restricted stock units. Motive offers benefits including health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution (all benefits are subject to eligibility requirements). Learn more about our benefits by visiting Motive Perks & Benefits The base compensation range for this role is: $127,000—$175,000 USD Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives. Please review our Candidate Privacy Notice here. UK Candidate Privacy Notice here. The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.

• Design and implement scalable, production-grade ETL/ELT pipelines • Take full ownership of the technical architecture, design, and implementation of the data platform and related tooling • Apply strong non-SQL programming skills (Python, PySpark, or similar) to data processing, automation, and pipeline development • Collaborate closely with stakeholders and engineering leaders to define and execute the data platform roadmap • Act as a subject matter expert, providing technical guidance and best practices to leadership and the wider engineering organization

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. Job Description Your Role: - Plan, manage, and execute releases across all environments - from development to production. - Identify technical and functional interdependencies between various tracks. - Coordinate with all development pods and stakeholders across programs. - Review application code, documentation, and perform pre/post deployment tasks. - Define release process for new data engineering applications. - Change management communication to all required stakeholders. - Execute release packages, step-by-step deployment guides, and command line instructions on production environment. - Support project timelines, clearly setting expectations, and realigning expectations internally as priorities change. - Develop a sound understanding of client’s needs: data conversion and migration requirements, environment management and build processes, deployment planning and execution, solution designs, systems integrations, technical architectures, and infrastructure architectures. Your Profile: - Execute deployment scripts and step-by-step instructions in test and production environments. - Comfortable with Command Line Interfaces. - Understanding of CI/CD, Git branching, packaging and DevOps pipelines. - Working knowledge of data warehousing and reporting technologies: Azure, Databricks, Unity Catalog, Python, Spark, PySpark, Airflow, MicroStrategy, Tableau. #LI-DC10 #LI-Remote Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

• Design, build, and optimize ETL/ELT pipelines in Azure cloud environments. • Develop scalable and reliable data workflows using Azure Data Factory (ADF) and other Azure data services. • Build and maintain data solutions leveraging Azure SQL and related cloud-native services. • Design and implement robust data models to support analytics, reporting, and downstream integrations. • Develop and support API-based integrations across internal and external systems. • Implement data models following modern Data Lakehouse or layered architecture principles. • Ensure data quality, consistency, and performance across ingestion, staging, and curated layers. • Collaborate with data architects, analysts, and business stakeholders to translate healthcare data requirements into scalable technical solutions. • Develop reusable data transformation logic and modular processing components. • Support deployment processes following CI/CD and DevOps best practices. • Monitor and optimize data workflows for performance, scalability, and reliability. • Contribute to data governance, security, and compliance practices relevant to healthcare environments.