Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: Datenanalyse und Prototyping mit Python in Azure Databricks unter Einsatz gangiger ML-Frameworks ...
Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: Datenanalyse und Prototyping mit Python in Azure Databricks unter Einsatz gangiger ML-Frameworks ...
Client Success Manager (MedInsight)
Appleton, WI · Remote
$788/wk
Experience with Databricks and cloud platforms, particularly Microsoft Azure * Prior exposure to ... Location This role is ideally based in Seattle, Washington, but remote work within the United ...
Client Success Manager (MedInsight)
Appleton, WI · Remote
$788/wk
Experience with Databricks and cloud platforms, particularly Microsoft Azure * Prior exposure to ... Location This role is ideally based in Seattle, Washington, but remote work within the United ...
Client Success Manager (MedInsight)
Brookfield, WI · Remote
$788/wk
Experience with Databricks and cloud platforms, particularly Microsoft Azure * Prior exposure to ... Location This role is ideally based in Seattle, Washington, but remote work within the United ...
Client Success Manager (MedInsight)
Brookfield, WI · Remote
$788/wk
Experience with Databricks and cloud platforms, particularly Microsoft Azure * Prior exposure to ... Location This role is ideally based in Seattle, Washington, but remote work within the United ...
Consulting Principal, AI Architect
Madison, WI · Remote
$122K - $194K/yr
Based on this role's business requirements, this is a remote position open to qualified applicants ... AWS, Azure, or GCP) and enterprise data platforms such as Snowflake, Databricks, or Microsoft ...
Consulting Principal, AI Architect
Madison, WI · Remote
$122K - $194K/yr
Based on this role's business requirements, this is a remote position open to qualified applicants ... AWS, Azure, or GCP) and enterprise data platforms such as Snowflake, Databricks, or Microsoft ...
Remote Azure Databricks information
Is Databricks a high paying job?
A remote Azure Databricks professional, such as a data engineer or data scientist, typically earns a competitive salary due to the specialized skills required, including expertise in cloud platforms, Spark, and data analytics. Salaries vary based on experience, location, and certifications but are generally above average for tech roles in data management and cloud computing.
What is the salary of Azure Databricks developer?
The salary of an Azure Databricks developer typically ranges from $90,000 to $140,000 annually, depending on experience, location, and certifications. Skilled professionals with expertise in Spark, cloud environments, and data engineering can command higher salaries.
What are Remote Azure Databricks jobs?
Remote Azure Databricks jobs are positions where professionals use Azure Databricks—a cloud-based analytics platform optimized for big data and machine learning—while working from a remote location. These roles typically involve tasks like building data pipelines, analyzing large datasets, developing and deploying machine learning models, and collaborating with teams virtually. Remote Azure Databricks professionals need strong skills in Spark, Python or Scala, and a good understanding of cloud computing. They often work as data engineers, data scientists, or analytics specialists, leveraging the platform’s capabilities to deliver data-driven insights for organizations.
Do Databricks have remote positions?
Remote positions for roles involving Azure Databricks are available, especially for data engineers, data scientists, and cloud specialists. Many companies offer remote work options for these roles, often requiring proficiency with cloud platforms, Spark, and data processing tools. Availability depends on the employer and specific job requirements.
What is the difference between Remote Azure Databricks vs Remote Data Engineer?
| Aspect | Remote Azure Databricks | Remote Data Engineer |
|---|---|---|
| Required Credentials | Azure certifications, Spark/Databricks knowledge | Data engineering certifications, SQL, cloud platform skills |
| Work Environment | Cloud-based, collaborative platform for data analytics | Data pipelines, database management, cloud environments |
| Industry Usage | Data analytics, AI, machine learning projects | Data pipeline development, ETL processes |
Remote Azure Databricks specialists focus on leveraging the Databricks platform for data analytics and machine learning, often working within cloud environments. Remote Data Engineers build and maintain data pipelines and infrastructure, frequently using cloud tools. While both roles require cloud and data skills, Azure Databricks roles are more centered on analytics and AI, whereas Data Engineers focus on data infrastructure and processing.
Is Azure Databricks in demand?
Azure Databricks professionals are in high demand due to the platform's widespread adoption for big data analytics and machine learning projects. Skills in Spark, cloud computing, and data engineering with Azure are valuable for these roles, which are often available in industries focusing on data-driven decision making.
What are the key skills and qualifications needed to thrive as a Remote Azure Databricks professional, and why are they important?
To thrive as a Remote Azure Databricks professional, you need strong expertise in data engineering, cloud computing, and proficiency in programming languages such as Python or Scala, typically supported by a relevant degree or certifications. Familiarity with Azure services, Databricks platform, Spark, and data pipeline orchestration tools is essential, often validated by Microsoft Azure or Databricks certifications. Excellent problem-solving, collaboration, and communication skills help you work effectively in distributed teams and convey complex technical concepts clearly. These skills and qualifications ensure robust data solutions, efficient remote teamwork, and the ability to leverage cloud analytics for business impact.
What are some common challenges faced by Remote Azure Databricks engineers, and how can they be managed?
Remote Azure Databricks engineers often encounter challenges related to collaboration and data security. Since Databricks projects typically involve large datasets and multiple stakeholders, coordinating work across time zones and ensuring secure data access can be complex. To manage these challenges, it's important to establish clear communication channels, use project management tools, and follow best practices in data governance. Regular team meetings and thorough documentation also help maintain alignment and ensure project success.
What are the most commonly searched types of Azure Databricks jobs in Wisconsin? The most popular types of Azure Databricks jobs in Wisconsin are:
What are popular job titles related to Remote Azure Databricks jobs in Wisconsin? For Remote Azure Databricks jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Remote Azure Databricks jobs in Wisconsin look for? The top searched job categories for Remote Azure Databricks jobs in Wisconsin are:
Contractor
Re-posted 9 days ago
Job description
Fur ein langfristig angelegtes Daten- und KI-Programm wird ein Databricks AI / ML Engineer (m/w/d) gesucht.
Ziel ist die Entwicklung, Implementierung und der Betrieb skalierbarer Machine-Learning- und LLM-Losungen auf Azure Databricks von der Datenaufbereitung uber Feature Engineering bis hin zu MLOps, Deployment und Monitoring.
Der Fokus liegt auf Big-Data-Engineering, ML/LLM-Workloads, MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem.
520 - 560 a day
Rahmenbedingungen
Start: Marz/April 2026
Laufzeit: 3 Jahre (optional verlangerbar bis max. 5 Jahre)
Auslastung: 100 %
Arbeitsmodell: Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote
Projektsprache: Deutsch und Englisch
Aufgaben:
Datenanalyse und Prototyping mit Python in Azure Databricks unter Einsatz gangiger ML-Frameworks
Entwicklung und Betrieb von Big-Data-Pipelines mit Apache Spark, Delta Lake und Databricks SQL
Durchfuhrung von Feature Engineering sowie Training, Versionierung und Deployment von Modellen mit Databricks MLflow
Entwicklung und Betrieb von ML- und LLM-Workloads auf Azure Databricks (inkl. Unity Catalog, Performance- und Kostenoptimierung)
End-to-End-Integration der Losungen in das Microsoft-Okosystem (z. B. API- und Schnittstellendesign, Orchestrierung mit Azure Functions und Logic Apps)
Aufbau und Weiterentwicklung von MLOps- und CI/CD-Pipelines fur automatisiertes Training, Testing, Deployment und Monitoring von ML- und LLM-Modellen sowie Agents
Durchfuhrung von Modell- und Datenmonitoring (Modellleistung, Daten-Drift, Bias) inklusive Wartungs- und Updateprozessen
Einsatz von AutoML-Tools zur Beschleunigung von Prototypen und Experimenten
Sicherstellung von Skalierbarkeit, Sicherheit und stabilen Betriebsprozessen der entwickelten Losungen
Fachliche Anforderungen:
Fundierte Kenntnisse in Datenanalyse und Prototyping mit Python in Azure Databricks
Erfahrung mit Machine-Learning-Frameworks wie TensorFlow, PyTorch und scikit-learn
Praktische Erfahrung im Big Data Engineering mit Apache Spark, Delta Lake und Databricks SQL
Kompetenz in Feature Engineering sowie Modell-Deployment mit managed Databricks MLflow
Erfahrung in der Entwicklung und dem Betrieb von ML- und LLM-Workloads auf Azure Databricks
Erfahrung mit End-to-End-Integrationen im Microsoft-Okosystem
Erfahrung im Aufbau von MLOps- und CI/CD-Pipelines fur ML- und LLM-Modelle sowie agentische Workflows
Erfahrung im Modell- und Datenmonitoring (Leistung, Drift, Bias) inklusive passender Wartungsstrategien
Praktische Erfahrung im Einsatz von AutoML-Tools
Vorhandensein einer eigenen, vom Produktivsystem des Auftraggebers getrennten Entwicklungsumgebung, die den aktuellen Standards fur Datensicherheit und Zugriffsschutz entspricht (inkl. Nachweis der Infrastruktur)
PLUS:
Erfahrung mit Data- und KI-Governance
Erfahrung in der Konzeption und Umsetzung agentischer Ansatze (Agenten, Multi-Agent-Systeme, agentische Workflows) mit Azure-Ressourcen
Erfahrung in der Umsetzung von End-to-End-Databricks-Projekten (von Datenaufbereitung und Feature Engineering uber Modelltraining und Deployment bis zu MLOps und Monitoring)
Branchenkenntnisse in der Energieindustrie
Strukturierte und analytische Arbeitsweise
Hohes Qualitatsbewusstsein und Verantwortungsbereitschaft
Sehr gute Kommunikationsfahigkeit gegenuber technischen und fachlichen Stakeholdern
Teamfahigkeit und Bereitschaft zur Wissensweitergabe
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