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Remote Databricks Data Engineer Jobs (NOW HIRING)

Data Engineer - Remote

Manhattan, NY · On-site +1

$126K - $151K/yr

Remote Seeking a highly skilled and motivated Data Engineer to join a dynamic team. As a key ... SQL * Databricks, Collibra, and/or Alteryx. * Familiarity with cloud-based data platforms ...

Data Engineer

$117K - $140K/yr

We are seeking to hire a Data Engineer to our team! Client: CTEC develops and delivers innovative ... Cloud Data Platform & Databricks Implementation: Build, optimize, and maintain data processing ...

The ideal candidate will work hands-on with modern cloud tools, Databricks, VHA Data Lake ... This position is fully remote, located in the United States. Responsibilities * Create cloud ...

Data Engineer

$117K - $140K/yr

We are seeking to hire a Data Engineer to our team! Client: CTEC develops and delivers innovative ... Cloud Data Platform & Databricks Implementation: Build, optimize, and maintain data processing ...

Data Engineer - Databricks

Mclean, VA · On-site +1

$125K - $160K/yr

Contributions We are looking for seasoned Data Engineer to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines in Databricks. We are looking for ...

Data Engineer - Databricks

Mclean, VA · On-site +1

$125K - $160K/yr

Overview We are looking for seasoned Data Engineer to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines in Databricks.We are looking for more than ...

While remote candidates will be considered, preference will be given to candidates located near a ... Familiarity with data governance, DevOps, CI/CD, infrastructure automation, monitoring, cost ...

While remote candidates will be considered, preference will be given to candidates located near a ... Familiarity with data governance, DevOps, CI/CD, infrastructure automation, monitoring, cost ...

Data Engineer

Minneapolis, MN · Remote

$117K - $140K/yr

... MN(Remote) Job Details: Candidate should be proficient in Data engineering skills : Data Bricks, ADF, Python, Pyspark, Azure services Data Engineer : Python, PySpark, Databricks with UC, Azure ...

Data Engineer

West Chester, PA · Remote

$108K - $130K/yr

Where You'll Work This role is remote; job seekers must reside in one of the following states to be ... Experience using Azure tools (Databricks, Data Factory, Delta Lake, Synapse, ADLS, PySpark, SQL ...

Data Engineer (Contract) (Remote)

Manhattan, NY · Remote

$126K - $151K/yr

Embracing a remote and flexible work philosophy, we offer our team the freedom to collaborate and ... Azure: Databricks, Data Factory, Azure SQL Database, Blob Storage, Event Hubs * GCP: BigQuery ...

$99K - $119K/yr

As a Data Engineer/Analyst, you will work closely with Medisolv clients to extract, transform and ... Databricks, Data Factory, Glue, Lambda, SQL Server). • Review existing data pipelines, data ...

Showing results 21-40

Remote Databricks Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do remote databricks data engineer jobs pay per year?

As of Aug 27, 2026, the average yearly pay for remote databricks data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a remote Databricks data engineer?

A Remote Databricks Data Engineer is a professional who designs, develops, and manages large-scale data processing systems using the Databricks platform, often working from a remote location. They focus on building data pipelines, integrating data sources, and optimizing workflows for analytics and machine learning, leveraging tools like Apache Spark within Databricks. These engineers collaborate with data scientists, analysts, and other stakeholders to ensure data is accessible, reliable, and scalable for business needs. Remote roles offer flexibility in work location while still requiring strong communication and technical skills.

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

To thrive as a Remote Databricks Data Engineer, you need a solid background in data engineering, strong programming skills in Python or Scala, and experience with big data frameworks, often supported by a degree in computer science or a related field. Proficiency with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valuable. Strong problem-solving abilities, effective remote communication, and collaboration skills set top performers apart in distributed teams. These skills and qualities ensure efficient data pipeline development, seamless integration, and successful project delivery in remote environments.

What are some common challenges faced by remote Databricks data engineers and how can they be addressed?

Remote Databricks Data Engineers often encounter challenges such as coordinating efficiently with distributed teams, managing access to secure data environments, and ensuring smooth pipeline deployments across different cloud platforms. To overcome these, it's important to leverage communication tools for regular check-ins, follow strict data governance protocols, and utilize collaborative features in Databricks such as shared notebooks and version control. Proactively documenting your work and staying updated with platform updates can also help streamline remote collaboration and problem-solving.
More about Remote Databricks Data Engineer jobs

What cities are hiring for Remote Databricks Data Engineer jobs?

Cities with the most Remote Databricks Data Engineer job openings:

What are the most commonly searched types of Databricks Data Engineer jobs?

The most popular types of Databricks Data Engineer jobs are:

What states have the most Remote Databricks Data Engineer jobs?

States with the most job openings for Remote Databricks Data Engineer jobs include:

Infographic showing various Remote Databricks Data Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer - Databricks, AWS, Python

Philadelphia, PA • Remote

$109K - $131K/yr

Full-time

Posted 24 days ago


Job description

Data Engineer – Databricks, AWS, Python
100% Remote / MUST interview on-site: Phila., PA  19103
$125,000 - $135,000/yrRole OverviewWe are seeking a Data Engineer to support the development, modernization, and delivery of data engineering assets, and the Yield Looker-to-Tableau migration, and Supply/Yield Data Engineering initiatives through the remainder of 2026. This role will focus on building reliable ETL pipelines, enhancing legacy jobs, supporting migration work, and delivering core data assets that feed analytics and reporting in Tableau Cloud.Key Responsibilities
  • Develop, test, and maintain ETL and data engineering jobs that bring data into Databricks and support downstream analytics and reporting.
  • Work with business and technical stakeholders to understand requirements and translate them into scalable, production-ready data pipelines.
  • Build and maintain pipelines across AWS, Databricks, and Snowflake environments.
  • Enhance existing legacy data engineering jobs as part of broader modernization and migration efforts.
  • Create and maintain technical documentation, technical specifications, test plans, and operational support materials.
  • Perform testing and quality assurance to validate data accuracy, pipeline reliability, and readiness for production deployment.
  • Use Terraform to provision, configure, and manage cloud infrastructure supporting data engineering workloads.
  • Set up and maintain CI/CD pipelines using Concourse, GitHub Actions, or similar tooling to enable smooth, repeatable deployments.
  • Troubleshoot pipeline issues, resolve defects quickly, and help ensure data jobs run reliably within expected service levels.
  • Provide post-delivery support, including issue investigation, defect resolution, and operational handoff.
  • Identify and mitigate risks, including single points of failure, reliability gaps, and operational dependencies.
  • Collaborate with engineers, analysts, and reporting teams to share knowledge, strengthen best practices, and improve delivery quality.
Project ScopeThe Data Engineer will augment capacity on the Supply/Yield Data Engineering team and support priority work related to INVENTORY ART, including migration activities and the development of core data pipelines and assets. These assets will support analytics and reporting used by Steve S.’s teams in Tableau Cloud. The role will also provide additional support for the Yield Looker-to-Tableau migration and related modernization efforts.Required Skills and Experience
  • Hands-on experience developing ETL, ELT, or data engineering pipelines in production environments.
  • Strong experience with Databricks, Spark-based processing, and modern data pipeline development.
  • Experience working with AWS cloud services and Snowflake data platforms.
  • Proficiency with infrastructure-as-code practices, preferably Terraform.
  • Experience implementing CI/CD practices using Concourse, GitHub Actions, or comparable deployment automation tools.
  • Ability to write clear technical specifications, documentation, and support materials.
  • Strong testing, quality assurance, troubleshooting, and operational support skills.
  • Ability to work collaboratively with cross-functional teams and translate requirements into working technical solutions.
Preferred Qualifications
  • Experience supporting analytics or BI migrations, especially from Looker to Tableau.
  • Experience developing data assets for Tableau Cloud reporting and analytics use cases.
  • Familiarity with supply, yield, inventory, or advertising-related data domains.
  • Experience modernizing or enhancing legacy data engineering jobs.
  • Strong understanding of operational reliability, risk mitigation, and single-point-of-failure reduction.

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