{"id":4201668,"url":"https://alion.io/job/slb-deployment-engineer","title":"Deployment Engineer","company":{"id":811720,"name":"SLB","domain":"slb.com","url":"https://alion.io/company/slb-2","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":82,"open_postings":162,"ghost_share":0,"stale_share":0.728,"repost_share":0,"time_to_fill_p50_days":51,"computed_at":"2026-11-12T10:38:37Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Confluence","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Python","optional":false},{"name":"SharePoint","optional":false},{"name":"SQL","optional":false},{"name":"Unstructured.io","optional":false},{"name":"CI/CD","optional":true},{"name":"Master Data Management","optional":true}],"status":"live","first_seen_at":"2026-11-12T06:50:00Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-12T22:28:13Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Title : Deployment Engineer\nJob Summary\nWe are seeking a highly motivated and technically strong Deployment Engineer to design, deploy, and\nmanage end - to- end industrial data pipelines and digital solutions built on Cognite Data Fusion (CDF) .\nThe successful candidate will be responsible for data onboarding, transformation, contextualization,\nquality validation, and data model management across a wide range of enterprise and industrial data\nsources.\nThis role requires a strong background in data engineering, industrial data analysis, cloud - based\ndeployments, and software delivery practices . The engineer will work closely with client stakeholders,\ndata owners, domain experts, software development teams, and solution architects to ensure high -\nquality data foundations that enable successful deployment of SLB digital solutions such as OptiFlow\nand OptiSite .\nSuccess in this role requires excellent analytical skills, strong communication capabilities, a passion for\nlearning new technologies, and the ability to rapidly adapt to the continuously evolving digital\ntechnologies by SLB & C ognite .\nKey Responsibilities\n1. Data Integration & Pipeline Deployment\nDesign, configure, and deploy end - to- end data ingestion pipelines into Cognite Data Fusion (CDF).\nIntegrate diverse data sources including:\no CSV and flat files\no SQL and relational databases\no PI Systems\no SCADA systems\no SAP systems\no Historians and operational databases\no Unstructured documents and files\no Other industrial and enterprise data sources\nEnsure reliable, scalable, and secure data ingestion architectures.\nTroubleshoot ingestion issues and optimize pipeline performance.\n2. Data Transformation & Contextualization\nTransform raw source data into consumable business and engineering datasets.\nPerform data contextualization and establish relationships between assets, events, time\nseries, documents, and engineering objects.\nDevelop mapping strategies that align source systems with enterprise data models.\nConfigure and maintain metadata structures and contextualization frameworks within CDF.\n3. Data Quality & Engineering Data Analysis\nAssess source data quality, completeness, accuracy, consistency, and readiness for\ndeployment.\nPerform detailed data profiling and validation activities.\nAnalyze sample datasets to identify data gaps, anomalies, inconsistencies, and missing\nrelationships.\nSLB-Private\nEstablish data quality checks and validation procedures throughout the deployment\nlifecycle.\nWork directly with client data owners to resolve data issues and improve data reliability.\nServe as a subject matter expert for engineering and operational data structures.\n4. CDF Data Modeling & Governance\nDesign, implement, and maintain data models within Cognite Data Fusion.\nDefine entities, relationships, metadata structures, and governance approaches.\nSupport lifecycle management of data models as business requirements evolve.\nEnsure data structures align with downstream application and analytics requirements.\n5. OptiFlow & OptiSite Deployment\nConfigure and deploy SLB digital solutions including OptiFlow and OptiSite.\nConfigure backend workflows, business logic, and application integrations.\nSupport UI configuration and solution customization based on customer requirements.\nValidate end - to- end functionality from source systems through application consumption.\nParticipate in solution testing, commissioning, and production deployment activities.\n6. Stakeholder Collaboration\nEngage with multiple client teams responsible for different data sources and operational\nsystems.\nGather technical requirements and source system information from stakeholders.\nFacilitate workshops, data discovery sessions, and deployment planning activities.\nCommunicate data findings, risks, and recommendations to technical and non - technical\naudiences.\nCollaborate closely with software developers, architects, project managers, and customer\nteams.\n7. Software Delivery & Cloud Operations\nWork closely with software development teams that consume CDF data for application\ndevelopment.\nUnderstand software development lifecycle (SDLC) methodologies and deployment\npractices.\nEnsure data structures support current and future application requirements.\nSupport cloud - based deployment and operational activities.\nContribute to continuous improvement of deployment methodologies and standards.\n8. Continuous Learning & Innovation\nStay current with new capabilities, updates, and best practices of OptiFlow, OptiSite, &\nCognite Data Fusion .\nRapidly learn and adopt emerging platform features and deployment approaches.\nEvaluate new technologies and tools that improve deployment efficiency and data quality.\nContribute to internal knowledge sharing and capability development initiatives.\nRequired Qualifications\nBachelor’s degree in computer science , Information Technology, Data Engineering, Engineering,\nor a related technical discipline.\n5+ years of experience in data engineering, deployment engineering, industrial digitalization, or\nrelated fields.\nExperience implementing enterprise - scale data integration and data management solutions.\nExperience working with cloud - based platforms and deployments.\nRequired Technical Skills\n1. Data Engineering\nStrong understanding of data integration, ETL/ELT, and data management practices.\nHands - on experience working with structured and unstructured data.\nExpertise in data profiling, cleansing, validation, and quality assessment.\nExperience with enterprise and industrial data architectures.\n2. Databases & SQL\nAdvanced SQL scripting and query optimization skills.\nExperience with relational databases and data warehousing concepts.\nAbility to investigate and troubleshoot complex data issues.\n3. Python & Automation\nIntermediate to advanced Python scripting skills.\nExperience developing automation scripts for data validation, transformation, and\ndeployment tasks.\nFamiliarity with APIs and integration frameworks.\n4. Cognite Data Fusion (Preferred)\nExperience with Cognite Data Fusion (CDF) or similar industrial data platforms.\nKnowledge of contextualization, data modeling, and industrial data management solutions.\n5. Industrial Systems\nExperience with one or more of the following:\nPI Systems (OSIsoft/AVEVA PI)\nSCADA systems\nSAP\nManufacturing Execution Systems (MES)\nIndustrial Historians\nEngineering Information Management Systems\nIndustrial IoT platforms\n6. Cloud Technologies\nExperience with cloud environments such as Azure, AWS, or Google Cloud Platform.\nUnderstanding of cloud deployment, security, networking, and operational concepts.\n7. Software Development\nUnderstanding of software development lifecycle (SDLC).\nFamiliarity with Agile delivery methodologies.\nExperience collaborating with software engineering and product development teams.\nWorking knowledge of Git and GitHub, including repository management, branching\nstrategies, commits, pull requests, code reviews, and issue tracking.\n8. Documentation & Knowledge Management\nExperience creating and maintaining technical documentation, deployment guides,\nrunbooks, and operational procedures.\nAbility to document data flows, system configurations, troubleshooting steps, and\ndeployment activities.\nExperience working with documentation and collaboration platforms such as Confluence,\nSharePoint, or similar knowledge management tools.\nKey Competencies:\nStrong analytical and problem-solving skills.\nExceptional attention to detail and data quality.\nExcellent stakeholder management and communication skills.\nAbility to work across multiple teams and organizational boundaries.\nStrong customer-facing and consulting capabilities.\nAbility to learn quickly and adapt to evolving technologies.\nSelf-driven with a high degree of ownership and accountability.\nAbility to manage competing priorities in dynamic project environments.\nPreferred Qualifications\nExperience deploying industrial digitalization solutions.\nExperience with SLB digital products such as OptiFlow and OptiSite.\nExperience in energy, manufacturing, process industries, or industrial operations.\nKnowledge of master data management and data governance practices.\nFamiliarity with DevOps and CI/CD deployment practices.\nUnderstanding of asset hierarchies, engineering data models, and operational data workflows.\nSuccess Measures\nThe successful candidate will:\nDeliver reliable and scalable CDF data pipelines.\nEnsure high standards of data completeness, correctness, and contextualization.\nSuccessfully deploy OptiFlow and OptiSite solutions for customers.\nBuild and maintain robust CDF data models supporting application development.\nEstablish trusted relationships with client stakeholders and data owners.\nEnable software development teams through high-quality, well-structured data foundations.\nContinuously adopt and leverage new capabilities within the CDF ecosystem to maximize customer value.\nJob Title : Deployment Engineer\nJob Summary\nWe are seeking a highly motivated and technically strong Deployment Engineer to design, deploy, and\nmanage end - to- end industrial data pipelines and digital solutions built on Cognite Data Fusion (CDF) .\nThe successful candidate will be responsible for data onboarding, transformation, contextualization,\nquality validation, and data model management across a wide range of enterprise and industrial data\nsources.\nThis role requires a strong background in data engineering, industrial data analysis, cloud - based\ndeployments, and software delivery practices . The engineer will work closely with client stakeholders,\ndata owners, domain experts, software development teams, and solution architects to ensure high -\nquality data foundations that enable successful deployment of SLB digital solutions such as OptiFlow\nand OptiSite .\nSuccess in this role requires excellent analytical skills, strong communication capabilities, a passion for\nlearning new technologies, and the ability to rapidly adapt to the continuously evolving digital\ntechnologies by SLB & C ognite .\nKey Responsibilities\n1. Data Integration & Pipeline Deployment\nDesign, configure, and deploy end - to- end data ingestion pipelines into Cognite Data Fusion (CDF).\nIntegrate diverse data sources including:\no CSV and flat files\no SQL and relational databases\no PI Systems\no SCADA systems\no SAP systems\no Historians and operational databases\no Unstructured documents and files\no Other industrial and enterprise data sources\nEnsure reliable, scalable, and secure data ingestion architectures.\nTroubleshoot ingestion issues and optimize pipeline performance.\n2. Data Transformation & Contextualization\nTransform raw source data into consumable business and engineering datasets.\nPerform data contextualization and establish relationships between assets, events, time\nseries, documents, and engineering objects.\nDevelop mapping strategies that align source systems with enterprise data models.\nConfigure and maintain metadata structures and contextualization frameworks within CDF.\n3. Data Quality & Engineering Data Analysis\nAssess source data quality, completeness, accuracy, consistency, and readiness for\ndeployment.\nPerform detailed data profiling and validation activities.\nAnalyze sample datasets to identify data gaps, anomalies, inconsistencies, and missing\nrelationships.\nSLB-Private\nEstablish data quality checks and validation procedures throughout the deployment\nlifecycle.\nWork directly with client data owners to resolve data issues and improve data reliability.\nServe as a subject matter expert for engineering and operational data structures.\n4. CDF Data Modeling & Governance\nDesign, implement, and maintain data models within Cognite Data Fusion.\nDefine entities, relationships, metadata structures, and governance approaches.\nSupport lifecycle management of data models as business requirements evolve.\nEnsure data structures align with downstream application and analytics requirements.\n5. OptiFlow & OptiSite Deployment\nConfigure and deploy SLB digital solutions including Opt...","description_format":"text","description_chars":17994,"description_truncated":true,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Petroleum & Mining Engineering","Oil & Gas"],"lifecycle":[{"event":"open","at":"2026-11-12T22:28:13Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":51,"reasons":["conf:1","win:early","comp:brand"],"computed_at":"2026-11-12T23:59:05Z"},"pay":null,"html_url":"https://alion.io/job/slb-deployment-engineer","json_url":"https://alion.io/job/slb-deployment-engineer.json","meta":{"generated_at":"2026-11-12T23:59:05Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":50704,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-13T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":811720},"rest":"https://alion.io/mcp/rest/get_company?id=811720"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fslb-deployment-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"free","price":{"credits":0,"usd":0},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fslb-deployment-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fslb-deployment-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/slb-deployment-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fslb-deployment-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":4201668}},{"tool":"search_jobs","arguments":{"company":"slb.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":4201668},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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