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Architect",{"name":283,"slug":284,"logo_url":10},[61],[19],200000,[25],{"aws":28,"gcp":30,"sql":28,"azure":28,"hbase":30,"kafka":30,"python":28,"airflow":30,"graphql":30,"kinesis":30,"mongodb":30,"cosmosdb":30,"dataflow":30,"dynamodb":30,"snowflake":28,"databricks":28},[33,32,197,67,198,297,459,460,461,181,462,463,464,465,182,466],"Kinesis","DataFlow","Airflow","DynamoDB","HBase","CosmosDB","GraphQL","DataBricks",{"nosql":30,"privacy":30,"security":30,"data quality":28,"cloud services":28,"data governance":28,"data management":28,"data integration":28,"data architecture":28,"relational modeling":28,"secure architecture":28,"scalable architecture":28,"master data management":30,"modern data warehousing":28,"cost-effective architecture":30,"real-time data distribution":30,"end-to-end data architecture":28},[201,469,470,410,82,471,472,473,474,475,476,477,478,479,480,481,482],"Data Management","Data Integration","Master Data Management","Security","Privacy","Cloud Services","Real-time Data Distribution","NoSQL","Modern Data Warehousing","Relational Modeling","End-to-end Data Architecture","Cost-effective Architecture","Scalable Architecture","Secure Architecture",{"id":484,"slug":485,"title":486,"raw_title":10,"is_featured":11,"company":487,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":490,"processed_country_iso_code_gmaps":491,"processed_home_office":357,"processed_salary_min":175,"processed_salary_max":176,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":492,"processed_employment_types":26,"processed_it_skills":493,"processed_it_skills_labels":494,"processed_job_expertise_skills":501,"processed_job_expertise_skills_labels":502,"max_cpc":54,"actual_cpc":54},59890,"senior-tech-lead-quantitative-analytics-engineering-lseg-employment-services-limited","Senior Tech Lead, Quantitative Analytics Engineering",{"name":488,"slug":489,"logo_url":10},"LSEG Employment Services Limited","lseg-employment-services-limited",[61],[19],[25],{"c#":30,"c++":30,"azure":28,"ci\u002Fcd":28,"python":28,"autogen":30,"devsecops":28,"langchain":30,"snowflake":30,"databricks":30,"mlops\u002Fllmops":28,"semantic kernel":30},[32,495,496,67,35,182,78,497,325,498,499,500],"C++","C#","DevSecOps","LangChain","Semantic Kernel","AutoGen",{"ai agents":28,"fixed income":30,"ai governance":28,"system design":28,"agile delivery":28,"ai\u002Fllm engineering":28,"alternative assets":30,"prompt engineering":28,"distributed systems":28,"portfolio analytics":30,"multi-asset analytics":30,"regulatory compliance":28,"software architecture":28,"engineering governance":28,"financial data platforms":30,"cloud-native architecture":28,"private markets analytics":28,"retrieval-augmented generation (rag)":28},[503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520],"Software Architecture","System Design","Distributed Systems","Cloud-Native Architecture","AI\u002FLLM Engineering","Prompt Engineering","Retrieval-Augmented Generation (RAG)","AI Agents","Agile Delivery","Engineering Governance","AI Governance","Regulatory Compliance","Private Markets Analytics","Alternative Assets","Portfolio Analytics","Financial Data Platforms","Fixed Income","Multi-Asset Analytics",{"id":522,"slug":523,"title":524,"raw_title":10,"is_featured":11,"company":525,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":528,"processed_country_iso_code_gmaps":529,"processed_home_office":357,"processed_salary_min":95,"processed_salary_max":530,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":531,"processed_employment_types":26,"processed_it_skills":532,"processed_it_skills_labels":533,"processed_job_expertise_skills":535,"processed_job_expertise_skills_labels":536,"max_cpc":54,"actual_cpc":54},52787,"data-science-manager-14101-arch-europe-insurance-services-ltd","Data Science Manager",{"name":526,"slug":527,"logo_url":10},"Arch Europe Insurance Services Ltd","arch-europe-insurance-services-ltd",[61],[19],130000,[25],{"sql":28,"azure":30,"python":28,"powerbi":30,"snowflake":30,"databricks":30},[32,33,534,35,182,67],"PowerBI",{"gbm":28,"glm":28,"data mining":28,"machine learning":28,"project management":30,"predictive modeling":28,"london market experience":28,"natural language processing":28,"insurance industry knowledge":28},[43,49,537,424,425,538,110,539,540],"Natural Language Processing","Data Mining","Insurance Industry Knowledge","London Market Experience",{"id":542,"slug":543,"title":544,"raw_title":10,"is_featured":11,"company":545,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":546,"processed_country_iso_code_gmaps":547,"processed_home_office":20,"processed_salary_min":226,"processed_salary_max":227,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":548,"processed_employment_types":26,"processed_it_skills":549,"processed_it_skills_labels":550,"processed_job_expertise_skills":552,"processed_job_expertise_skills_labels":553,"max_cpc":54,"actual_cpc":54},57818,"visualisation-engineer-2136gb00-howden-uk-brokers-limited","Visualisation Engineer",{"name":222,"slug":223,"logo_url":10},[],[19],[25],{"dax":28,"sql":30,"azure":29,"power bi":28,"databricks":29,"data modelling":28},[231,551,259,33,67,35],"DAX",{"data analysis":28,"data governance":30,"stakeholder management":28,"data quality management":30,"insurance industry knowledge":30,"financial services experience":30,"business requirements analysis":28},[554,46,555,82,539,556,348],"Business Requirements Analysis","Data Quality Management","Financial Services Experience",{"image_path":558,"content_de":559,"content_en":572,"composite_key":585,"last_updated":586},"\u002Fimages\u002Fskill\u002Fdatabricks.webp",{"tab1":560,"tab2":563,"tab3":566,"tab4":569},{"title":561,"content":562},"Bedeutung & Relevanz","Databricks hat im [Vereinigtes Königreich](\u002Fsearch) eine herausragende strategische Bedeutung für die Versicherungsbranche entwickelt. Als führende Unified Data Analytics-Plattform ermöglicht Databricks Versicherungsunternehmen die Verarbeitung und Analyse riesiger Datenmengen in Echtzeit – eine entscheidende Fähigkeit in einem Markt, der zunehmend datengesteuert arbeitet. Die Plattform unterstützt Versicherer bei der Entwicklung fortschrittlicher [Risikomanagement](\u002Fjobs-by-expertise\u002Frisk-management)-Modelle und präziserer [Finanzanalyse](\u002Fjobs-by-expertise\u002Ffinancial-analysis), was direkt zu verbesserten Underwriting-Entscheidungen und präziseren Prämienkalkulationen führt.\n\nIm [Vereinigtes Königreich](\u002Fsearch) nutzen Versicherungsunternehmen Databricks insbesondere für komplexe Back-Testing-Prozesse und die Entwicklung von Pricing-Modellen. Die Fähigkeit, maschinelles Lernen und statistische Modellierung nahtlos in bestehende Workflows zu integrieren, macht Databricks zu einem unverzichtbaren Werkzeug für Wettbewerbsfähigkeit und Innovation. Unternehmen wie [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) setzen die Plattform ein, um ihre Datenanalyse-Fähigkeiten zu skalieren und datengesteuerte Entscheidungen in allen Geschäftsbereichen zu treffen.",{"title":564,"content":565},"Top-Branchen & Standorte","Im [Vereinigtes Königreich](\u002Fsearch) konzentriert sich die Nachfrage nach Databricks-Expertise primär auf die [Versicherungsbranche](\u002Fjobs-by-industry\u002Finsurance), wo die Plattform für datenintensive Prozesse wie Underwriting, Schadenregulierung und Risikomodellierung eingesetzt wird. Die Versicherungsindustrie nutzt Databricks zur Verarbeitung großer Datenquellen und zur Entwicklung präziser statistischer Modelle, die fundamentale Geschäftsentscheidungen unterstützen.\n\nGeografisch gesehen sind [London](\u002Fjobs-in-london) und [Birmingham](\u002Fjobs-in-birmingham) die wichtigsten Standorte für Databricks-Profis. [London](\u002Fjobs-in-london) als globales Finanzzentrum beherbergt zahlreiche internationale Versicherungsunternehmen und spezialisierte Technologieteams, während [Birmingham](\u002Fjobs-in-birmingham) als wachsender Technologie-Hub zunehmend Databricks-Expertise für regionale Versicherungsanbieter und FinTech-Unternehmen nachfragt. Diese Standorte bieten exzellente Karrieremöglichkeiten für Fachkräfte mit Databricks-Kenntnissen in der dynamischen Versicherungslandschaft des [Vereinigtes Königreich](\u002Fsearch).",{"title":567,"content":568},"Gefragte Skills & Arbeitgeber","Führende Unternehmen wie [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) suchen im [Vereinigtes Königreich](\u002Fsearch) aktiv nach Databricks-Experten, die über spezifisches Fachwissen in verwandten Bereichen verfügen. Besonders gefragt sind Kenntnisse in Back Testing, Underwriting und [Datenanalyse](\u002Fjobs-by-expertise\u002Fdata-analysis), die direkt mit den Databricks-Funktionalitäten verknüpft werden können.\n\nZu den wichtigsten gefragten Expertisen gehören [Risikomanagement](\u002Fjobs-by-expertise\u002Frisk-management), technische Preisgestaltung, Pricing-Modell-Entwicklung und die Entwicklung von Schadenmodellen. Versicherungsunternehmen benötigen Databricks-Profis, die maschinelles Lernen (GBMs) und statistische Modellierung (GLMs) für präzise Risikobewertungen und Geschäftsausgabenanalysen einsetzen können. Die Fähigkeit, große Datenquellen zu managen und Inflationsannahmen in komplexe Modelle zu integrieren, macht Databricks-Experten zu wertvollen Assets für Unternehmen, die datengesteuerte Entscheidungen in der kompetitiven Versicherungslandschaft des [Vereinigtes Königreich](\u002Fsearch) treffen müssen.",{"title":570,"content":571},"Karriere & Entwicklung","Karrierewege für Databricks-Experten im [Vereinigtes Königreich](\u002Fsearch) bieten vielfältige Entwicklungsmöglichkeiten in der Versicherungsbranche. Einstiegspositionen beginnen oft als Data Engineer oder Data Analyst, mit Aufstiegsmöglichkeiten zu Senior Data Scientist, Machine Learning Engineer oder Head of Data Analytics. Die Kombination aus Databricks-Kenntnissen und spezialisiertem Versicherungswissen in Bereichen wie Underwriting oder [Risikomanagement](\u002Fjobs-by-expertise\u002Frisk-management) eröffnet exzellente Karrierechancen.\n\nUm Databricks zu erlernen, empfehlen sich die offizielle Databricks Academy, praktische Projekte mit [Python](\u002Fjobs-by-skill\u002Fpython) und [SQL](\u002Fjobs-by-skill\u002Fsql), sowie die Vertiefung verwandter IT-Skills wie SAS, Advanced Excel und spezialisierter Versicherungssoftware. Die Integration von maschinellem Lernen und statistischer Modellierung in bestehende [Prozessverbesserung](\u002Fjobs-by-expertise\u002Fprocess-improvement)-Workflows ist entscheidend für den beruflichen Erfolg. Fachkräfte können sich durch Zertifizierungen in Databricks und kontinuierliche Weiterbildung in relevanten Bereichen wie Preisadjustierungsanalyse und Large Data Source Management positionieren, um in der dynamischen Versicherungsbranche des [Vereinigtes Königreich](\u002Fsearch) wettbewerbsfähig zu bleiben.",{"tab1":573,"tab2":576,"tab3":579,"tab4":582},{"title":574,"content":575},"Strategic Importance","Databricks has emerged as a critical platform in the [Vereinigtes Königreich](\u002Fsearch)'s financial landscape, particularly within the [insurance](\u002Fjobs-by-industry\u002Finsurance) sector. Its strategic importance lies in enabling companies like [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) to process and analyze vast datasets efficiently, which is essential for advanced [risk management](\u002Fjobs-by-expertise\u002Frisk-management) and [financial analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis). In the UK, where regulatory demands and competitive pressures are high, Databricks facilitates real-time [data analysis](\u002Fjobs-by-expertise\u002Fdata-analysis) and supports [machine learning](\u002Fjobs-by-expertise\u002Fmachine-learning) applications, such as [GBMs](\u002Fjobs-by-expertise\u002Fgbms) and [GLMs](\u002Fjobs-by-expertise\u002Fglms), for accurate [technical pricing](\u002Fjobs-by-expertise\u002Ftechnical-pricing) and [pricing model development](\u002Fjobs-by-expertise\u002Fpricing-model-development). This capability is vital for developing robust [actuarial assumptions](\u002Fjobs-by-expertise\u002Factuarial-assumptions) and [inflation assumptions](\u002Fjobs-by-expertise\u002Finflation-assumptions), helping insurers mitigate risks and optimize profitability. By leveraging Databricks, UK firms can enhance [process improvement](\u002Fjobs-by-expertise\u002Fprocess-improvement) initiatives, streamline [claims management](\u002Fjobs-by-expertise\u002Fclaims-management), and conduct thorough [back testing](\u002Fjobs-by-expertise\u002Fback-testing) to validate models against historical data. The platform's integration with tools like [Python](\u002Fjobs-by-skill\u002Fpython) and [SQL](\u002Fjobs-by-skill\u002Fsql) further amplifies its relevance, making it indispensable for data-driven decision-making in a dynamic market. As the UK insurance industry evolves, Databricks' role in supporting [statistical modelling](\u002Fjobs-by-expertise\u002Fstatistical-modelling) and [large data source management](\u002Fjobs-by-expertise\u002Flarge-data-source-management) ensures that companies remain agile and compliant, driving innovation and sustainable growth.",{"title":577,"content":578},"Top Industries & Locations","In the [Vereinigtes Königreich](\u002Fsearch), Databricks is highly sought after in key industries and urban centers, with the [insurance](\u002Fjobs-by-industry\u002Finsurance) sector leading the demand. Major hubs like [London](\u002Fjobs-in-london) and [Birmingham](\u002Fjobs-in-birmingham) are at the forefront, hosting numerous firms that rely on Databricks for advanced analytics. [London](\u002Fjobs-in-london), as a global financial epicenter, sees extensive use in [insurance](\u002Fjobs-by-industry\u002Finsurance) companies for tasks such as [risk assessment](\u002Fjobs-by-expertise\u002Frisk-assessment) and [market analysis](\u002Fjobs-by-expertise\u002Fmarket-analysis), leveraging the platform to handle complex datasets. [Birmingham](\u002Fjobs-in-birmingham), with its growing tech and financial services ecosystem, also embraces Databricks for [financial modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) and [project management](\u002Fjobs-by-expertise\u002Fproject-management) in insurance contexts. Beyond these, the platform's applicability spans [banking](\u002Fjobs-by-industry\u002Fbanking) and [asset management](\u002Fjobs-by-industry\u002Fasset-management) industries, where it supports [portfolio management](\u002Fjobs-by-expertise\u002Fportfolio-management) and [sales](\u002Fjobs-by-expertise\u002Fsales) analytics. In the UK, the convergence of [insurance](\u002Fjobs-by-industry\u002Finsurance) with technologies like [generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) and [artificial intelligence tools](\u002Fjobs-by-skill\u002Fartificial-intelligence-tools) further drives adoption in these locations, enabling firms to enhance [business expense analysis](\u002Fjobs-by-expertise\u002Fbusiness-expense-analysis) and [price adjustment analysis](\u002Fjobs-by-expertise\u002Fprice-adjustment-analysis). This geographic and industrial focus underscores Databricks' role in powering data-intensive operations, with [London](\u002Fjobs-in-london) and [Birmingham](\u002Fjobs-in-birmingham) serving as critical nodes for talent and innovation in the UK's financial services landscape.",{"title":580,"content":581},"In-Demand Skills & Employers","Top employers in the [Vereinigtes Königreich](\u002Fsearch), such as [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance), actively seek professionals skilled in Databricks, often requiring complementary expertise like [back testing](\u002Fjobs-by-expertise\u002Fback-testing), [underwriting](\u002Fjobs-by-expertise\u002Funderwriting), and [data analysis](\u002Fjobs-by-expertise\u002Fdata-analysis). These companies value Databricks for its ability to support [risk engineering](\u002Fjobs-by-expertise\u002Frisk-engineering) and [claims management](\u002Fjobs-by-expertise\u002Fclaims-management), integrating it with [technical pricing](\u002Fjobs-by-expertise\u002Ftechnical-pricing) and [pricing model development](\u002Fjobs-by-expertise\u002Fpricing-model-development) workflows. In the UK insurance sector, expertise in [actuarial assumptions](\u002Fjobs-by-expertise\u002Factuarial-assumptions) and [inflation assumptions](\u002Fjobs-by-expertise\u002Finflation-assumptions) is crucial, and Databricks enhances these through robust [machine learning](\u002Fjobs-by-expertise\u002Fmachine-learning) capabilities, including [GBMs](\u002Fjobs-by-expertise\u002Fgbms) and [GLMs](\u002Fjobs-by-expertise\u002Fglms). Employers also prioritize skills in [statistical modelling](\u002Fjobs-by-expertise\u002Fstatistical-modelling) and [large data source management](\u002Fjobs-by-expertise\u002Flarge-data-source-management), as these are integral to [business expense analysis](\u002Fjobs-by-expertise\u002Fbusiness-expense-analysis) and [price adjustment analysis](\u002Fjobs-by-expertise\u002Fprice-adjustment-analysis). Beyond [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance), other key players in the UK market leverage Databricks for [financial markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) analysis and [process improvement](\u002Fjobs-by-expertise\u002Fprocess-improvement), often pairing it with IT skills like [SAS](\u002Fjobs-by-skill\u002Fsas), [SQL](\u002Fjobs-by-skill\u002Fsql), and [Python](\u002Fjobs-by-skill\u002Fpython). The demand extends to tools such as [WTW Radar](\u002Fjobs-by-skill\u002Fwtw-radar) and [WTW Emblem](\u002Fjobs-by-skill\u002Fwtw-emblem), highlighting the platform's synergy with industry-specific software. This combination of Databricks proficiency and related expertise makes candidates highly valuable in the UK job market, particularly for roles focused on innovation and risk mitigation in insurance.",{"title":583,"content":584},"Career & Development","Pursuing a career with Databricks in the [Vereinigtes Königreich](\u002Fsearch) offers diverse paths, especially in the [insurance](\u002Fjobs-by-industry\u002Finsurance) industry, where roles often evolve from data analysts to senior positions in [risk management](\u002Fjobs-by-expertise\u002Frisk-management) or [financial analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis). To build expertise, start by mastering foundational IT skills like [SQL](\u002Fjobs-by-skill\u002Fsql), [Python](\u002Fjobs-by-skill\u002Fpython), and [SAS](\u002Fjobs-by-skill\u002Fsas), which are essential for leveraging Databricks in tasks such as [data analysis](\u002Fjobs-by-expertise\u002Fdata-analysis) and [statistical modelling](\u002Fjobs-by-expertise\u002Fstatistical-modelling). In the UK, professionals can advance by specializing in [machine learning](\u002Fjobs-by-expertise\u002Fmachine-learning) applications, including [GBMs](\u002Fjobs-by-expertise\u002Fgbms) and [GLMs](\u002Fjobs-by-expertise\u002Fglms), to support [technical pricing](\u002Fjobs-by-expertise\u002Ftechnical-pricing) and [pricing model development](\u002Fjobs-by-expertise\u002Fpricing-model-development). Learning platforms like Databricks through online courses or certifications can enhance capabilities in [large data source management](\u002Fjobs-by-expertise\u002Flarge-data-source-management) and [back testing](\u002Fjobs-by-expertise\u002Fback-testing), critical for roles in [underwriting](\u002Fjobs-by-expertise\u002Funderwriting) and [claims management](\u002Fjobs-by-expertise\u002Fclaims-management). Additionally, gaining experience with tools such as [WTW Radar](\u002Fjobs-by-skill\u002Fwtw-radar), [WTW Emblem](\u002Fjobs-by-skill\u002Fwtw-emblem), and [advanced Excel](\u002Fjobs-by-skill\u002Fadvanced-excel) complements Databricks proficiency, enabling effective [business expense analysis](\u002Fjobs-by-expertise\u002Fbusiness-expense-analysis) and [price adjustment analysis](\u002Fjobs-by-expertise\u002Fprice-adjustment-analysis). Career development often involves focusing on [actuarial assumptions](\u002Fjobs-by-expertise\u002Factuarial-assumptions) and [inflation assumptions](\u002Fjobs-by-expertise\u002Finflation-assumptions), with opportunities to lead [project management](\u002Fjobs-by-expertise\u002Fproject-management) initiatives in UK firms. By continuously updating skills in [generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) and related technologies, individuals can secure growth in high-demand areas, ensuring long-term success in the evolving financial landscape of the UK.","skill:databricks:gb","2026-08-17T09:02:37.436861+02:00",{"industry":588,"employment_type":603,"expertise_skills":609,"it_skills":668,"salary_currency":731,"processed_working_hours":733},[589,593,597,600],{"key":590,"label":591,"count":592},"insurance","Insurance",12,{"key":594,"label":595,"count":596},"financial markets infrastructure","Financial Markets Infrastructure",5,{"key":598,"label":599,"count":596},"data","Data",{"key":601,"label":602,"count":29},"financial services","Financial Services",[604,607],{"key":26,"label":605,"count":606},"PERMANENT",17,{"key":255,"label":608,"count":29},"TEMPORARY",[610,613,616,618,620,623,625,628,630,632,634,637,640,642,644,647,649,651,653,656,658,661,663,665],{"key":611,"label":82,"slug":611,"count":612},"data-governance",7,{"key":614,"label":46,"slug":614,"count":615},"data-analysis",6,{"key":617,"label":49,"slug":617,"count":615},"machine-learning",{"key":619,"label":201,"slug":619,"count":596},"data-architecture",{"key":621,"label":622,"slug":621,"count":28},"responsible-ai","Responsible Ai",{"key":624,"label":239,"slug":624,"count":30},"data-modeling",{"key":626,"label":627,"slug":626,"count":30},"project-management","Project management",{"key":629,"label":236,"slug":629,"count":30},"data-visualization",{"key":631,"label":43,"slug":631,"count":30},"predictive-modeling",{"key":633,"label":444,"slug":633,"count":29},"security-architecture",{"key":635,"label":636,"slug":635,"count":29},"uk-regulatory-environment","Uk Regulatory Environment",{"key":638,"label":639,"slug":638,"count":29},"mlopsllmops","Mlops\u002FLlmops",{"key":641,"label":470,"slug":641,"count":29},"data-integration",{"key":643,"label":108,"slug":643,"count":29},"technical-pricing",{"key":645,"label":646,"slug":645,"count":29},"ai-governance","Ai Governance",{"key":648,"label":539,"slug":648,"count":29},"insurance-industry-knowledge",{"key":650,"label":405,"slug":650,"count":29},"predictive-analytics",{"key":652,"label":45,"slug":652,"count":29},"data-pipeline",{"key":654,"label":655,"slug":654,"count":29},"glms","Glms",{"key":657,"label":109,"slug":657,"count":29},"back-testing",{"key":659,"label":660,"slug":659,"count":29},"gbms","Gbms",{"key":662,"label":208,"slug":662,"count":29},"data-privacy",{"key":664,"label":410,"slug":664,"count":29},"data-quality",{"key":666,"label":667,"slug":666,"count":29},"glm","Glm",[669,671,674,676,680,683,685,688,691,694,697,699,701,704,706,709,712,714,717,719,722,724,727,729],{"key":670,"label":35,"slug":670,"count":4},"databricks",{"key":672,"label":32,"slug":672,"count":673},"python",15,{"key":675,"label":33,"slug":675,"count":673},"sql",{"key":677,"label":678,"slug":677,"count":679},"ms-azure","MS Azure",10,{"key":681,"label":682,"slug":681,"count":615},"aws","Aws",{"key":684,"label":182,"slug":684,"count":596},"snowflake",{"key":686,"label":687,"slug":686,"count":596},"ms-powerbi","MS PowerBI",{"key":689,"label":690,"slug":689,"count":28},"gcp","Gcp",{"key":692,"label":693,"slug":692,"count":28},"ms-excel","MS Excel",{"key":695,"label":696,"slug":695,"count":30},"wtw-radar","Wtw Radar",{"key":698,"label":292,"slug":698,"count":30},"java",{"key":700,"label":39,"slug":700,"count":30},"jira",{"key":702,"label":703,"slug":702,"count":30},"wtw-emblem","Wtw Emblem",{"key":705,"label":297,"slug":705,"count":30},"kafka",{"key":707,"label":708,"slug":707,"count":30},"pyspark","Pyspark",{"key":710,"label":711,"slug":710,"count":30},"sql-server","Sql Server",{"key":713,"label":38,"slug":713,"count":30},"ms-office",{"key":715,"label":716,"slug":715,"count":29},"postgresql","Postgresql",{"key":718,"label":70,"slug":718,"count":29},"terraform",{"key":720,"label":721,"slug":720,"count":29},"aws-glue","Aws Glue",{"key":723,"label":294,"slug":723,"count":29},"microsoft-fabric",{"key":725,"label":726,"slug":725,"count":29},"azure-openai","Azure Openai",{"key":728,"label":232,"slug":728,"count":29},"r",{"key":730,"label":296,"slug":730,"count":29},"athena",[732],{"key":22,"label":22,"count":4},[734],{"key":25,"label":25,"count":4},{"total":736,"jobs":737},0,[]]