Deployment Engineer

Overview

Design, deploy and manage end-to-end industrial data pipelines and digital solutions built on Cognite Data Fusion (CDF), including data onboarding, transformation, contextualization, quality validation and data model management, and the deployment of SLB digital solutions such as OptiFlow and OptiSite.

What you'll do

• Design, configure and deploy end-to-end data ingestion pipelines into Cognite Data Fusion (CDF).
• Integrate diverse data sources including CSV and flat files, SQL and relational databases, PI Systems, SCADA systems, SAP systems, historians and operational databases, unstructured documents and files, and other industrial and enterprise data sources.
• Ensure reliable, scalable and secure data ingestion architectures.
• Troubleshoot ingestion issues and optimize pipeline performance.
• Transform raw source data into consumable business and engineering datasets.
• Perform data contextualization and establish relationships between assets, events, time series, documents and engineering objects.
• Develop mapping strategies that align source systems with enterprise data models.
• Configure and maintain metadata structures and contextualization frameworks within CDF.
• Assess source data quality, completeness, accuracy, consistency and readiness for deployment.
• Perform detailed data profiling and validation activities.
• Analyze sample datasets to identify data gaps, anomalies, inconsistencies and missing relationships.
• Establish data quality checks and validation procedures throughout the deployment lifecycle.
• Work directly with client data owners to resolve data issues and improve data reliability.
• Serve as a subject matter expert for engineering and operational data structures.
• Design, implement and maintain data models within Cognite Data Fusion.
• Define entities, relationships, metadata structures and governance approaches.
• Support lifecycle management of data models as business requirements evolve.
• Ensure data structures align with downstream application and analytics requirements.
• Configure and deploy SLB digital solutions including OptiFlow and OptiSite.
• Configure backend workflows, business logic and application integrations.
• Support UI configuration and solution customization based on customer requirements.
• Validate end-to-end functionality from source systems through application consumption.
• Participate in solution testing, commissioning and production deployment activities.
• Engage with multiple client teams responsible for different data sources and operational systems.
• Gather technical requirements and source system information from stakeholders.
• Facilitate workshops, data discovery sessions and deployment planning activities.
• Communicate data findings, risks and recommendations to technical and non-technical audiences.
• Collaborate closely with software developers, architects, project managers and customer teams.
• Work closely with software development teams that consume CDF data for application development.
• Understand software development lifecycle (SDLC) methodologies and deployment practices.
• Ensure data structures support current and future application requirements.
• Support cloud-based deployment and operational activities.
• Contribute to continuous improvement of deployment methodologies and standards.
• Stay current with new capabilities, updates and best practices of OptiFlow, OptiSite and Cognite Data Fusion.
• Rapidly learn and adopt emerging platform features and deployment approaches.
• Evaluate new technologies and tools that improve deployment efficiency and data quality.
• Contribute to internal knowledge sharing and capability development initiatives.

What you'll need

• Bachelor's degree in computer science, Information Technology, Data Engineering, Engineering or a related technical discipline.
• 5+ years of experience in data engineering, deployment engineering, industrial digitalization or related fields.
• Experience implementing enterprise-scale data integration and data management solutions.
• Experience working with cloud-based platforms and deployments.
• Strong understanding of data integration, ETL/ELT and data management practices.
• Hands-on experience working with structured and unstructured data.
• Expertise in data profiling, cleansing, validation and quality assessment.
• Experience with enterprise and industrial data architectures.
• Advanced SQL scripting and query optimization skills.
• Experience with relational databases and data warehousing concepts.
• Ability to investigate and troubleshoot complex data issues.
• Intermediate to advanced Python scripting skills.
• Experience developing automation scripts for data validation, transformation and deployment tasks.
• Familiarity with APIs and integration frameworks.
• Experience with one or more of: PI Systems (OSIsoft/AVEVA PI), SCADA systems, SAP, Manufacturing Execution Systems (MES), industrial historians, engineering information management systems, industrial IoT platforms.
• Experience with cloud environments such as Azure, AWS or Google Cloud Platform.
• Understanding of cloud deployment, security, networking and operational concepts.
• Understanding of software development lifecycle (SDLC).
• Familiarity with Agile delivery methodologies.
• Experience collaborating with software engineering and product development teams.
• Working knowledge of Git and GitHub, including repository management, branching strategies, commits, pull requests, code reviews and issue tracking.
• Experience creating and maintaining technical documentation, deployment guides, runbooks and operational procedures.
• Ability to document data flows, system configurations, troubleshooting steps and deployment activities.
• Experience with documentation and collaboration platforms such as Confluence, SharePoint or similar knowledge management tools.
• Strong analytical and problem-solving skills, with exceptional attention to detail and data quality.
• Excellent stakeholder management and communication skills; ability to work across multiple teams and organizational boundaries.
• Strong customer-facing and consulting capabilities; ability to learn quickly, adapt to evolving technologies and manage competing priorities.

Nice to have

• Experience with Cognite Data Fusion (CDF) or similar industrial data platforms.
• Knowledge of contextualization, data modeling and industrial data management solutions.
• Experience deploying industrial digitalization solutions.
• Experience with SLB digital products such as OptiFlow and OptiSite.
• Experience in energy, manufacturing, process industries or industrial operations.
• Knowledge of master data management and data governance practices.
• Familiarity with DevOps and CI/CD deployment practices.
• Understanding of asset hierarchies, engineering data models and operational data workflows.

Details

• Location: Pune, India.