Senior Data Engineer - Azure, Databricks & ML Pipelines | Remote - Remote-Stelle

Toptal sucht Senior Data Engineer - Azure, Databricks & ML Pipelines | Remote: Senior-Niveau, das Unternehmen erwartet also, dass Sie die Entscheidungen selbst treffen. Die Stelle liegt im Bereich Daten und Analytics und ist vollständig remote. Das Unternehmen schränkt den Wohnort der Kandidatin nicht ein, Sie können sich also von überall bewerben.

Die wichtigsten in der Anzeige genannten Werkzeuge sind: Python, SQL, Machine Learning. Der Lebenslauf sollte konkrete Beispiele genau dieser Fähigkeiten zeigen.

Das Unternehmen hat keine Zahl veröffentlicht, das klärt sich im Gespräch. Zu den Arbeitszeiten stellt die Anzeige keine Bedingung.

Diese Stelle hat eine automatische Prüfung durchlaufen: Anzeigen, die eine ausländische Arbeitserlaubnis, Visa-Sponsoring, eine bestimmte Staatsangehörigkeit oder den Wohnsitz in einem genannten Land verlangen, kommen nicht auf die Liste.

Headquarters: Remote

URL: https://www.toptal.com/

About the Role

We're looking for a Senior Data Engineer to design, build, and maintain scalable data pipelines and ML-ready infrastructure on Azure and Databricks. This is a hands-on engineering role: you'll own the full data pipeline lifecycle - ingestion, transformation, orchestration, and deployment - while supporting machine learning workflows with clean, reliable data. If you're comfortable owning infrastructure decisions and writing production-quality Python at scale, this role is built for that.

What You'll Do

* Design, build, and maintain data pipelines using Databricks and Azure-native data services

* Develop and optimize ETL/ELT processes to support analytics and machine learning workloads

* Build and maintain CI/CD pipelines for data engineering and ML deployment workflows

* Write clean, efficient, production-quality Python for data processing and pipeline automation

* Support machine learning teams with well-structured, high-quality datasets and feature pipelines

* Design and manage data architecture across Azure services (e.g., Azure Data Factory, Azure Data Lake, Azure Synapse)

* Monitor pipeline performance, troubleshoot data quality issues, and implement reliability improvements

* Implement data governance, security, and access control best practices

* Collaborate with data scientists, analysts, and software engineers to align data infrastructure with business needs

* Participate in code reviews, architecture discussions, and technical planning

What You Bring

* Strong hands-on experience with Azure cloud data services

* Proven experience building and maintaining pipelines on Databricks

* Solid experience designing and managing CI/CD pipelines for data or ML workflows

* Strong Python skills for data engineering and pipeline development

* Working knowledge of machine learning workflows and how data engineering supports them

* Experience with SQL and relational/distributed data systems

* Understanding of data pipeline orchestration, monitoring, and reliability practices

* Strong problem-solving skills and ability to work independently on complex data infrastructure challenges

* Solid communication skills for collaborating with data science and engineering teams

Nice to Have

* Experience with MLOps practices and tools (MLflow, Azure ML)

* Familiarity with Spark internals and performance tuning within Databricks

* Experience with infrastructure-as-code (Terraform, Bicep, ARM templates)

* Exposure to real-time/streaming data pipelines (Kafka, Event Hubs, Structured Streaming)

* Relevant Azure or Databricks certifications

Why This Role

* Full pipeline ownership: Own data infrastructure end to end, from ingestion through ML-ready delivery

* Modern data stack: Work with Azure and Databricks, leading platforms in enterprise data engineering

* Cross-functional impact: Directly enable machine learning and analytics outcomes, not just move data

* Flexibility: Remote-friendly engagement structure

How to Apply

Ready to bring your data engineering expertise to Azure and Databricks-powered ML infrastructure? Apply through Toptal here: https://www.toptal.com/talent/apply

 

To apply: https://weworkremotely.com/remote-jobs/toptal-senior-data-engineer-azure-databricks-ml-pipelines-remote