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CompassMSP
CompassMSP
201 – 500 Darbinieki
B2BKiberdrošībaKonsultācijas
CompassMSP ir Amerikas Savienotajās Valstīs bāzēts pārvaldīto pakalpojumu sniedzējs, kas apkalpo uzņēmumus un regulētās nozares, nodrošinot pārvaldītus IT pakalpojumus, mākoņinfrastruktūru, kiberdrošību un konsultāciju kompetenci. Uzņēmuma pakalpojumi ietver pilnībā pārvaldītu un kopīgi pārvaldītu IT, Microsoft 365 atbalstu, Azure un AWS mākoņstratēģiju un migrāciju, diennakts palīdzības dienesta darbību, dublēšanu un avārijas atjaunošanu, vienotos sakarus, vCISO konsultācijas, reaģēšanu uz incidentiem, aizsardzību pret izspiedējprogrammatūru un gatavību nodrošināt atbilstību tādiem ietvariem kā HIPAA, HITRUST un CMMC. CompassMSP strādā arī pie mākslīgā intelekta modernizācijas un droša mākslīgā intelekta iniciatīvām. Uzņēmuma darbību visā valstī atbalsta vairāki reģionālie biroji.
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Vakances uzņēmumā

Remote Data Analytics Engineer

Build and maintain CompassMSP’s Azure lakehouse and data portal for MSP operations, while moving reporting from legacy SQL Server and Power BI. The role also covers data pipelines, dashboards, internal applications, and AI capabilities.

USAmerikas Savienotās ValstisAttālinātiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuAnalītikas inženieris
AzureDockerJavaScriptMākonisPandasPythonSparkSQL

Apraksts

  • Direct roughly 60% of your work to backend development, 30% to front-end development, and 10% to business systems as needed.
  • Build and maintain CompassMSP’s internal data platform and lakehouse in Microsoft Azure.
  • Bring reporting together in the lakehouse and data portal.
  • Move active reports to the governed lakehouse and data portal as you phase out legacy SQL Server reporting and Power BI.
  • Keep data pipelines healthy and support the end-to-end data flow.
  • Create data models, reports, and dashboards that business users can trust.
  • Develop internal applications on the data platform.
  • Help build an AI layer that lets users ask questions about data in plain language.
  • Create reports on data health.
  • Work with the Director of Data & Analytics and colleagues across Service Delivery, Finance, Sales, Client Success, and Leadership.
  • Use AI coding assistants for development, code review, data exploration, and documentation, while taking responsibility for the quality and accuracy of your work.

Prasības

  • At least 3 years of experience in data engineering, analytics engineering, or a related role.
  • Strong SQL skills, including T-SQL, with the ability to read and refactor stored procedures, views, and SQL Agent jobs.
  • Strong Python skills for data work and experience with DuckDB, Spark, pandas, or similar tools.
  • Hands-on experience with a cloud data platform, preferably Azure, and Delta Lake or a similar table format.
  • Sound data modeling skills, including dimensional models, medallion architecture, slowly changing dimensions, and conformed metrics.
  • Experience building ELT pipelines from REST APIs and SaaS systems.
  • Experience migrating reports or data workloads between platforms, with a structured process for reconciliation and sign-off.
  • Experience creating reports and dashboards for business users and turning broad questions into precise metrics.
  • Comfort using Git, pull requests, and code review.
  • A habit of reconciling figures before relying on them.
  • Preferred: Experience in an MSP or IT services company, or with ConnectWise, Sage Intacct, or HiBob data.
  • Preferred: Experience administering or using data from Salesforce, Gong, Cognism, or HubSpot.
  • Preferred: In-depth Power BI experience, including DAX, semantic models, REST and XMLA APIs, and usage metrics.
  • Preferred: Experience retiring legacy systems, including mapping dependencies, coordinating stakeholders, and archiving.
  • Preferred: Experience with Microsoft Fabric, Azure Container Apps, or Docker.
  • Preferred: Web development experience with JavaScript, HTML, and CSS, plus Azure Static Web Apps or App Service.
  • Preferred: Experience with data quality and observability tools such as dbt tests, Great Expectations, or custom checks.
  • Preferred: Experience building with LLM APIs, retrieval-augmented generation, or semantic layers.
  • Preferred: Experience with CI/CD using GitHub Actions.

Priekšrocības

  • Competitive annual salary
  • Quarterly bonuses
  • Progressive paid time off
  • Medical, dental, vision, life, and disability coverage available
  • 401(k) with company match
  • Career development and coaching

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