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Data and analytics

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

Toptal

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Posted: (27 days ago)Active until: until 7 September 2026

Senior Data Engineer - Azure, Databricks & ML Pipelines | Remote - Data and analytics, remote

Toptal is hiring a Senior Data Engineer - Azure, Databricks & ML Pipelines | Remote - a senior role, so the employer expects you to make the calls yourself. The role sits in Data and analytics and is fully remote. The company places no restriction on where the candidate lives, so you can apply from anywhere.

The main tools named in the advert are: Python, SQL, Machine Learning. Your CV should show concrete examples of exactly these skills.

The employer did not publish a figure; that is settled at interview. The advert sets no condition on working hours.

This vacancy passed an automated check: the list excludes any advert requiring a foreign work permit, visa sponsorship, a particular citizenship, or residence in a specific country.

In brief

Company
Toptal
Category
Data and analytics
Who may apply
From anywhere in the world
Work mode
Fully remote
Level
Senior
Tools
Python, SQL, Machine Learning
Posted
29 July 2026 (27 days ago)
Active
until 7 September 2026
Source
We Work Remotely

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The employer's description

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

The text is kept in the employer's original language, because that is the language you will apply in.

This vacancy was published on We Work Remotely. Original advert (We Work Remotely)

Frequently asked questions about this job

Can I apply for Senior Data Engineer - Azure, Databricks & ML Pipelines | Remote from where I live?

Yes. Toptal accepts candidates for this vacancy from anywhere in the world, so you need no work permit for a foreign country. The advert passed an automated check: had the employer required a work permit, visa sponsorship or residence in a specific country, it would not be on this board.

What pay is stated?

Toptal did not publish pay for this vacancy. Most remote adverts publish no figure; it is settled at interview.

How do I apply?

You apply directly to the employer, through the original advert published on We Work Remotely. Donator takes no applications, charges no commission and stores no CV.

What kind of vacancy is this?

A fully remote role in Data and analytics. Hybrid adverts and anything requiring office attendance are not published on this board.

Free certificates for this vacancy

This advert asks for Python, SQL, Machine Learning. Below are the free credentials that cover exactly those tools.

All free certificates: AI and data

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