Sr. Data Engineer & Scientist

Robertson,-Anschutz,-Schneid,-Crane-; Boca Raton (FL); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Robertson,-Anschutz,-Schneid,-Crane- seeks a Senior Data Engineer & Scientist to design, build, and maintain enterprise-scale data platforms, data pipelines, analytics solutions, and AI-enabled applications that support business operations and decision-making.

Reporting to the Director of AI & Automation, the role combines data engineering, data science, analytics, and AI integration to establish a modern data ecosystem with trusted data intelligence, advanced analytics, and AI-driven insights.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Data Analytics, Information Systems, Engineering, or a related field (Master's degree preferred).
• 5+ years of professional experience in Data Engineering, Data Science, Analytics Engineering, Automation or a related technical discipline.
• Proven experience designing and implementing enterprise data platforms, data warehouses, lakehouses, and scalable ETL/ELT solutions.
• Strong hands-on expertise in SQL, Python, Spark, and modern cloud-based data platforms.
• Experience building scalable data pipelines, enterprise data integrations, and reporting datasets.
• Working knowledge of machine learning, predictive analytics, statistical modeling, and data science methodologies.
• Experience supporting AI initiatives, including Generative AI, Document Intelligence, NLP, RAG, or related AI technologies.
• Strong understanding of data governance, metadata management, data quality, security, and compliance principles.
• Excellent analytical, problem-solving, and stakeholder communications skills.
• Experience working within Microsoft Azure, AWS, or Google Cloud environments and modern DevOps practices.

Responsibilities

• Design, develop, and maintain enterprise data platforms, including datalakes, warehouses, lakehouses, semantic models, and medallion architectures (Bronze, Silver, Gold).
• Build and optimize scalable ETL/ELT pipelines using Azure Databricks, Azure Data Factory, Snowflake, SQL, Python, Spark, AWS, GCP.
• Integrate data from internal applications, third-party systems, APIs, automation platforms, and external data sources.
• Develop enterprise data models, master data structures, and reusable datasets for reporting, analytics, automation, and AI initiatives.
• Support data migration, modernization, and consolidation across business applications.
• Implement and maintain data governance, cataloging, lineage, data quality, auditing, observability, and security standards.
• Analyze structured and unstructured data to identify trends, patterns, opportunities, and actionable insights.
• Develop predictive models and ML solutions to improve operational outcomes and decision-making; create data products, dashboards, KPIs, and metrics.
• Support AI initiatives including Generative AI, IDP, and Retrieval-Augmented Generation (RAG) architectures.
• Prepare, curate, and optimize enterprise datasets for ML and AI workloads.
• Develop and maintain data pipelines supporting LLMs, Document Intelligence, vector databases, and AI platforms.
• Enable enterprise search, knowledge management, and contextual data access capabilities.
• Collaborate with AI engineers to integrate AI capabilities into business applications and workflows.
• Participate in full solution lifecycle from requirements through deployment and support.
• Ensure compliance with security, privacy, governance, and regulatory requirements.
• Monitor and optimize platform performance, scalability, reliability, and cost efficiency.
• Collaborate with cross-functional teams to deliver high-quality, business-focused solutions.
• Contribute to technical standards, best practices, documentation, and continuous improvement initiatives.

Skills

SQL

Python

Spark

Cloud Platforms

Education

Bachelor's degree in CS/DS/Analytics/IS/Engineering

Tools

Azure Databricks

Azure Data Factory

Microsoft Fabric

Snowflake

SQL

Python

Spark

AWS

GCP

Job description

The SeniorDataEngineer&Scientist isahighlyskilledtechnicalprofessionalresponsiblefordesigning,building,andmaintainingenterprise-scaledataplatforms,datapipelines,analyticssolutions,andAI-enabledapplicationsthatsupportbusinessoperationsanddecision-makingacrosstheorganization.

ReportingtotheDirectorofAI&Automation,thisrolecombinesdataengineering,datascience,analytics,andAIintegrationresponsibilitiestoestablishamoderndataecosystemthatenablestrusteddataintelligence,advancedanalytics,predictiveinsights,andAI-drivensolutions.Theidealcandidateishands-on,delivery-focused,andpassionateabouttransformingdataintobusinessvaluewhilesupportingtheadoptionofAIandautomationcapabilitiesacrosstheenterprise.

TherolecollaboratescloselywithAIEngineers,AutomationEngineers,BIAnalysts,businessleaders,legaldomainexperts,andotherstakeholderstodeliverscalable,secure,andreliabledatasolutionsthatimproveoperationalefficiencyanddriveinnovation.

WorkArrangement:

Hybrid in Boca Raton, Florida

KeyResponsibilities:

• Design,develop,andmaintainenterprisedataplatforms,includingdatalakes,warehouses,lakehouses,semanticmodels,andmedallionarchitectures(Bronze,Silver,andGoldlayers).


• BuildandoptimizescalableETL/ELTpipelinesusingtechnologiessuchasAzureDatabricks,AzureDataFactory,MicrosoftFabric,Snowflake,SQL,Python,Spark,AWS,GCP,andsimilarcloud-nativetechnologies.


• Integratedatafrominternalapplications,third-partysystems,APIs,automationplatforms,andexternaldatasources.


• Developenterprisedatamodels,masterdatastructures,andreusabledatasetsthatsupportreporting,analytics,automation,andAIinitiatives.


• Supportdatamigration,modernization,andconsolidationeffortsacrossbusinessapplications.


• Implementandmaintaindatagovernance,cataloging,lineage,dataquality,auditing,observability,andsecuritystandards.

DataScience&AdvancedAnalytics

• Analyzestructuredandunstructureddatasetstoidentifytrends,patterns,opportunities,andactionablebusinessinsights.


• Developpredictivemodels,statisticalanalyses,andmachinelearningsolutionsthatimproveoperationaloutcomesanddecision-making.Createandsupportdataproducts,dashboards,KPIs,andperformancemetricsforbusinessandexecutivestakeholders.


• Supportexperimentation,modelevaluation,performancemonitoring,andcontinuousimprovementofanalyticsandmachinelearningsolutions.


• SupportthedevelopmentofAI-enabledapplications,GenerativeAIsolutions,IntelligentDocumentProcessing(IDP),andRetrieval-AugmentedGeneration(RAG)architectures.


• Prepare,curate,andoptimizeenterprisedatasetsformachinelearning,generativeAI,andagenticAIworkloads.


• DevelopandmaintaindatapipelinessupportingLargeLanguageModels(LLMs),DocumentIntelligence,vectordatabases,andAIplatforms.


• Enableenterprisesearch,knowledgemanagement,andcontextualdataaccesscapabilities.


• CollaboratewithAIEngineerstointegrateAIcapabilitiesintobusinessapplicationsandworkflows.


• Participateinthefullsolutionlifecycle,includingrequirementsgathering,design,development,testing,deployment,monitoring,andsupport.


• Ensurecompliancewithenterprisesecurity,privacy,governance,andregulatoryrequirements.


• Monitorandoptimizeplatformperformance,scalability,reliability,andcostefficiency.


• Collaboratewithcross-functionalteamstodeliverhigh-quality,business-focusedsolutions.


• Contributetotechnicalstandards,bestpractices,documentation,andcontinuousimprovementinitiatives.

RequiredQualifications

• Bachelor'sdegreeinComputerScience,DataScience,DataAnalytics,InformationSystems,Engineering,orarelatedfield(Master'sdegreepreferred).


• 5+yearsofprofessionalexperienceinDataEngineering,DataScience,AnalyticsEngineering,Automationorarelatedtechnicaldiscipline.


• Provenexperiencedesigningandimplementingenterprisedataplatforms,datawarehouses,lakehouses,andscalableETL/ELTsolutions.


• Stronghands-onexpertiseinSQL,Python,Spark,andmoderncloud-baseddataplatforms.


• Experiencebuildingscalabledatapipelines,enterprisedataintegrationsolutions,andreportingdatasets.


• Workingknowledgeofmachinelearning,predictiveanalytics,statisticalmodeling,anddatasciencemethodologies.


• ExperiencesupportingAIinitiatives,includingGenerativeAI,DocumentIntelligence,NLP,RAG,orrelatedAItechnologies.


• Strongunderstandingofdatagovernance,metadatamanagement,dataquality,security,andcomplianceprinciples.


• Excellentanalytical,problem-solving,andstakeholdercommunicationskills.


• ExperienceworkingwithinMicrosoftAzure,AWS,orGoogleCloudenvironmentsandmodernDevOpspractices.