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Remote Sql Data Engineer Jobs in Wisconsin (NOW HIRING)

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... Data-Pipelines mit Apache Spark , Delta Lake und Databricks SQL Durchfuhrung von Feature ...

Business Data Analyst

Milwaukee, WI · On-site +1

$55K - $120K/yr

  • Medical

  • Retirement

  • PTO

Partner with developers and data engineers to ensure delivered solutions meet documented ... Proficiency in writing SQL queries for data analysis and validation. * Excellent oral and written ...

Remote bevorzugt, gelegentliche Vor-Ort-Termine nach Absprache 400 - 450 a day Aufgaben Aufbau und ... Betrieb von End-to-End Data-Science- und ML-Workflows Implementierung von ML ...

The Data Warehouse Engineer I is part of a team dedicated to supporting Network Health's Enterprise ... Experience with T-SQL development, SSIS development, and database troubleshooting skills required ...

The Data Warehouse Engineer I is part of a team dedicated to supporting Network Health's Enterprise ... Experience with T-SQL development, SSIS development, and database troubleshooting skills required ...

The Data Warehouse Engineer I is part of a team dedicated to supporting Network Health's Enterprise ... Experience with T-SQL development, SSIS development, and database troubleshooting skills required ...

The Data Warehouse Engineer I is part of a team dedicated to supporting Network Health's Enterprise ... Experience with T-SQL development, SSIS development, and database troubleshooting skills required ...

Develop data cleansing and remediation recommendations for data irregularities. Establish key ... in SQL and Python (3+ years) Notes: 90-100% remote but can require staff to come onsite as ...

  • Retirement

... programming, along with the ability to translate complex findings into clear business ... Master-level tool knowledge (e.g., SQL, Python, AWS, DataRobot, AnyLogic, and other simulation ...

  • Retirement

... programming, along with the ability to translate complex findings into clear business ... Master-level tool knowledge (e.g., SQL, Python, AWS, DataRobot, AnyLogic, and other simulation ...

  • Retirement

... programming, along with the ability to translate complex findings into clear business ... Master-level tool knowledge (e.g., SQL, Python, AWS, DataRobot, AnyLogic, and other simulation ...

  • Retirement

... programming, along with the ability to translate complex findings into clear business ... Master-level tool knowledge (e.g., SQL, Python, AWS, DataRobot, AnyLogic, and other simulation ...

Software Engineer III - IntelliScript (Remote)

Brookfield, WI · On-site +1

$54.50 - $73.25/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a software engineer focused on prescription, health, and medical record data solutions, you ... Strong proficiency in C# (.NET) and SQL, with experience working with large-scale data systems

Software Engineer III - IntelliScript (Remote)

Brookfield, WI · On-site +1

$54 - $72.50/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a software engineer focused on prescription, health, and medical record data solutions, you ... Strong proficiency in C# (.NET) and SQL, with experience working with large-scale data systems

The Senior Data Modeler leads collaboration with data architects, data engineers, and business ... Proficiency with SQL, strong understanding of data pipeline and data warehousing principles and ...

Showing results 21-40

Remote Sql Data Engineer information

What does a remote SQL data engineer do?

A Remote SQL Data Engineer designs, develops, and maintains databases and data pipelines using SQL technologies, all while working from a remote location. They are responsible for ensuring data is collected, stored, and retrieved efficiently and securely. Their work often involves writing complex SQL queries, optimizing database performance, and collaborating with other teams to support data-driven decision-making. They may also manage ETL (Extract, Transform, Load) processes and help integrate data from multiple sources to support analytics and business intelligence.

What are the key skills and qualifications needed to thrive as a remote SQL data engineer?

To thrive as a Remote SQL Data Engineer, you need strong proficiency in SQL, data modeling, and ETL processes, often supported by a degree in computer science or a related field. Experience with database management systems like Microsoft SQL Server, PostgreSQL, or MySQL, as well as tools such as SSIS or cloud platforms like AWS and Azure, is typically required. Excellent problem-solving skills, attention to detail, and effective communication are essential soft skills for collaborating remotely and conveying technical information. These abilities are important to ensure accurate data management, seamless data integration, and reliable performance in a distributed work environment.

How does a remote SQL data engineer typically collaborate with cross-functional teams to ensure data integrity and project success?

As a Remote SQL Data Engineer, you will frequently work with data analysts, software developers, and business stakeholders to understand data requirements, design robust database solutions, and troubleshoot data issues. Collaboration often occurs through virtual meetings, project management tools, and shared documentation platforms. Clear communication and proactive updates are essential, as you'll need to ensure that data pipelines are reliable and align with the needs of both technical and non-technical team members. Regular code reviews and knowledge-sharing sessions help maintain data integrity and foster a cohesive remote team environment.

What is the difference between Remote Sql Data Engineer vs Remote Data Analyst?

AspectRemote Sql Data EngineerRemote Data Analyst
Required SkillsSQL, ETL, data modeling, database managementSQL, data visualization, reporting, statistical analysis
CertificationsSQL certifications, data engineering coursesData analysis certifications, Tableau, Excel
Work EnvironmentData pipelines, database systems, cloud platformsData interpretation, dashboards, business insights
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, consulting

Remote Sql Data Engineers focus on building and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require SQL skills and often overlap in data handling, but differ in their core responsibilities and tools used.

What are the most commonly searched types of Sql Data Engineer jobs in Wisconsin?

The most popular types of Sql Data Engineer jobs in Wisconsin are:

What are popular job titles related to Remote Sql Data Engineer jobs in Wisconsin?

For Remote Sql Data Engineer jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Remote Sql Data Engineer jobs in Wisconsin look for?

The top searched job categories for Remote Sql Data Engineer jobs in Wisconsin are:

What cities in Wisconsin are hiring for Remote Sql Data Engineer jobs?

Cities in Wisconsin with the most Remote Sql Data Engineer job openings:

Databricks AI / ML Engineer (m/w/d)

Qualysoft

On-site, Remote

Contractor

Re-posted 16 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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