{"id":3851524,"url":"https://alion.io/job/southern-company-operations-data-engineering-analyst","title":"Operations Data Engineering Analyst","company":{"id":2607898,"name":"Southern Company","domain":"southern.com","url":"https://alion.io/company/southern-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Birmingham, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"DNP3","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Statistical Process Control","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-11-06T00:44:32Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-08T09:45:23Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"OPERATIONS DATA ENGINEERING ANALYST\nJOB SUMMARY\nThispositionwillfunctionaspartoftheSouthernPowerMonitoring&Diagnostics(M&D)Center,which\nprovidesremotemonitoringanddiagnosticsupporttotheSPCfleetofgas,solar,wind,andenergystorage assets.\nTheOperationsDataEngineeringAnalystsupportsbothoperationaldatainfrastructureandAI/MLdata readiness. The role assists the PI System Administrator with daily operation, maintenance, and expansion/migration of SPC’s AVEVA PI andAspenTech IP.21 historianenvironments, including tag\nmanagement,AssetFramework(AF)configuration,analyticsdeployment,PIVisiondevelopment,dataquality monitoring, and proactive remediation. The role also extracts, transforms, curates, and delivers clean,\nstructureddatasetsfromPIandIP.21intodownstreamdataengineeringplatformssuchasDatabricksto supportM&D’sgrowingAIandmachinelearningportfolio,includingiSightanomalydetection,predictive analytics models, and AI agents.\nInshort,thisroleownsthedatajourneyfromrawsensoringestioninPIthroughcurated,AI-readydatasets\n-ensuringtheM&Dteamalwayshastrusted,high-quality,well-engineereddatatopowerbothreal-time monitoring and advanced analytics.\nThispositionwillcloselyinterfacewiththeAvevaPI/AspenTechIP.21SystemAdministrator,M&DAnalysts, AI/MLAnalysts,RenewablePerformanceEngineers,Renewable,Gas,andCommercialOperations,theSPC Technology Organization, SCADA teams, and plant personnel.\nMAJOR JOBRESPONSIBILITIES\nPI/IP.21SystemSupport\nTagManagement- SupportthePI/IP.21Administratorinthecreation,modification,scaling,and\n\ndecommissioningofPI/IP.21tagsacrossgas,solar,wind,andenergystorageassets.Ensuretagnaming conventions, point types, and compression settings are consistent with fleet-wide standards.\nAssetFramework (AF)Configuration- Create,modify,anddeleteAFelements,attributes,templates, and hierarchies to reflect fleet changes (new sites, equipment swaps, decommissions). Maintain AF structureintegrityacrossallOEMs(solarinverters,windturbines,gasturbines,batteries,andBOP equipment).\n\nAFAnalyticsDeployment- Develop,test,anddeployPIAFAnalytics(calculatedattributes,rollup expressions, eventframes)in testandproductionenvironments. Validate analytic outputsagainst expected results prior to production deployment.\n\nDataQualityMonitoring&ProactiveRemediation- ContinuouslymonitordataqualityacrossPIand IP.21 platforms - identifying stale tags, flatlined signals, bad values, communication failures, scaling\nerrors,andmissingdata.Proactivelyremediateissuesbeforetheyimpactdownstreamanalytics, dashboards, or AI models. Support data surrogation processes where needed.\n\nPI Vision Development & Maintenance - Design, develop, and maintain real-time PI Vision screens and dashboardsforfleetmonitoring,equipmenthealth,dataquality,andKPItracking.Updatedisplaysasnew sites are onboarded or fleet configurations change.\n\nSiteOnboardingSupport- AssistthePI/IP.21Administratorwithintegratingnewgenerationandstorage sites into the PI/IP.21 System, including interface/connector configuration, tag provisioning, AF buildout, initial data validation, and PI Vision screen creation.\n\nData Query Support for Other Teams - Serve as a resource for operations, performance, and analytics teamswhoneedtoextractdatafromPI/IP.21.ProvidesupportandguidanceusingPIDataLink,IP.21Excel Connector, Python, SQL, PI Web API, and PI Connect to enable self-service data access and integration\n\nwithdownstreamtools.\nTroubleshooting- Assistindiagnosingandresolvingdataflowissues,interfacecommunicationfailures, archivegaps,andsystemerrorswithinthePIandIP.21environments.Escalateinfrastructure-levelissues to the PI/IP.21 Administrator or IT as appropriate.\n\nDataEngineering&AI/MLDataReadiness\nDatasetCuration&Cleaning- Buildandmaintainrepeatabledatacurationpipelinesthatclean, validate,deduplicate,aligntimestamps,handlemissingvalues,andresolvedataqualityissues-\n\nproducingtrusted,well-documenteddatasetsforAI/MLmodeltrainingandinferenceinDatabricks.\nAI/ML Data Requirements Engineering - Partner directly with theAI/MLAnalyst tounderstand model inputrequirements,featuredefinitions,labelingschemas,datafrequencyneeds,andqualitythresholds.\n\nTranslatetheserequirementsintoactionabledataengineeringtasksanddeliverdatasetsthatmeet model specifications.\nModel-ReadyDataValidation- ValidatecurateddatasetsagainstAImodelinputspecifications-\n\ncheckingforcompleteness,balance,featuredrift,outliers,andschemacompliancein/outsideDatabricks. Flag and resolve data issues before they enter training or inference pipelines.\nPipelineMonitoring&Maintenance- Monitorhealthandperformanceofdatapipelines,alertingon failures, latency, ordata quality degradation.Continuously improve pipeline efficiency, reliability, and scalability as the fleet and AI use cases grow.\n\nCollaboration&ContinuousImprovement\nCross-FunctionalCollaboration- BuildandmaintainstrongworkingrelationshipswiththePI/IP.21\n\nAdministrator,AI/MLAnalysts,M&DAnalysts,RenewablesPerformanceEngineers,Renewable,Gas,and Commercial Operations, SCADA teams, Technology Organization developers, and plant personnel.\nDocumentation- MaintainthoroughdocumentationofPIconfigurations,AFstructures,taginventories, data pipeline architectures, dataset catalogs, and standard operating procedures.\n\nBestPractices&LessonsLearned- Incorporateindustrybestpractices,lessonslearned,andfeedback into daily operations. Participate in fleet-wide standardization efforts and data governance initiatives.\n\nContinuousLearning- StaycurrentonAVEVAPISystemupdates,dataengineeringbestpractices (Databricks), AI/ML pipeline methodologies, and relevant industry trends.\n\nJOB REQUIREMENTS\nEducation\nBachelor'sdegreeinEngineering(Electrical,Computer,InstrumentationsandControls),Computer Science, Data Science, or a related technical field - required.\n\nMaster'sdegreeinEngineering(Electrical,Computer,Instrumentation&Controls),ComputerScience, Data Science, or a related technical field - preferred.\n\nExperience\nRequired\nPISystemHands-On: 2-3yearsofhands-onexperiencewithAVEVAPISystem,includingPIDataArchive, PI Asset Framework (AF), PI Vision, and PI Interfaces/Connectors.\n\nPython: ProficientinPythonfordataextraction,transformation,pipelinedevelopment,andautomation (Pandas, NumPy, Web API calls, scripting).\n\nSQL: ProficientinSQLfordataquerying,integration,andmanipulationacrossrelationaldatabasesand data platforms.\n\nDataEngineeringPlatform: FamiliarwithDatabricks,ApacheSpark,orequivalentdataengineering platforms - including ETL/ELT pipeline development, Delta Lake, and feature store concepts.\n\nDataQuality&Governance: Experiencewithdataqualitymonitoring,validation,remediation,and surrogation in an operational/industrial context.\n\nPreferred\nPIDataAccessTools: WorkingknowledgeofPIDataLink,PIWebAPI,andPIConnectfordataextraction and downstream integration.\n\nPIAFAnalytics: ExperiencedevelopinganddeployingAFAnalytics,calculatedattributes,eventframes, and notifications.\n\nAI/MLPipelineUnderstanding: FoundationalunderstandingofMLmodeldeploymentpipelines- includingfeatureengineering,datalabeling,modeltrainingdatarequirements,andinferencedata delivery.\n\nDataVisualization/BI: ExperiencewithPowerBI,Tableau,orsimilarBItoolsfordashboarddevelopment and operational reporting.\n\nEnergySector: Experienceinpowergeneration,renewables,orutilitiesoperations.\n\nPlus\nOtherData Historians: ExperiencewithAspenTechIP.21, dataPARC,eDNA etc.\n\nSCADASystems: FamiliaritywithIgnition/otherSCADAsystems.\n\nCommunicationsProtocols: OPCDA/UA,DNP3,Modbusprotocolsanddataacquisitionarchitectures.\n\nPIAccreditation: AVEVA/OSIsoftPISystemaccreditation.\n\nBEHAVIORALATTRIBUTES\nMustbeabletomaketimelydecisions,applyseasonedjudgment,anddisplaypersonalresponsibility.\n\nDemonstrateSouthernCompanyValues:SafetyFirst,IntentionalInclusion,ActwithIntegrity,and Superior Performance.\n\nBeateamplayer-abletoquicklybuildgood,productiveworkingrelationshipswiththePI Administrator, AI/ML team, operations teams, and technology partners.\n\nDetail-orientedandproactive-anticipatedataqualityissuesbeforetheyimpactdownstream consumers.\n\nResults-orientedself-starterthatcanworkindependentlywhilecontributingtoteamobjectives.\nCreativelysolveissues,thinkoutsidethebox,andfindinnovativewaystobridgeoperationaldataand AI/ML requirements.\n\nIntellectuallycurious-eagertolearnnewtools,platforms,andmethodologiesacrossbothPISystem administration and data engineering domains.","description_format":"text","description_chars":8313,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Nuclear Energy","Fossil Fuels","Power Grid"],"lifecycle":[{"event":"open","at":"2026-11-06T03:35:19Z"}],"visa":[{"country":"US","licensed_sponsor":true,"adverts_offering_sponsorship_24m":0,"sanctioned_now":false,"evidence":"H-1B filings in 12 months: 3","filings_12m":3,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":77500,"route":null,"cap_exempt":false,"checked_at":"2026-11-08T10:45:15+00:00","sources":["US Department of Labor: 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