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Databricks Jobs in Pennsylvania (NOW HIRING)

Databricks Engineer and Architect

Radnor, PA · Hybrid

$58.50 - $76.75/hr

Significant Databricks experience is required. You'll partner closely with risk analysts, quantitative researchers, and technology leaders to migrate business-owned processes into robust, production ...

Databricks Engineer and Architect

Radnor, PA · On-site

$58.50 - $76.75/hr

Significant Databricks experience is required. You'll partner closely with risk analysts, quantitative researchers, and technology leaders to migrate business-owned processes into robust, production ...

Databricks Engineer and Architect

Radnor, PA · Hybrid

$58.50 - $76.75/hr

Significant Databricks experience is required. You'll partner closely with risk analysts, quantitative researchers, and technology leaders to migrate business-owned processes into robust, production ...

Showing results 41-60

Databricks information

See Pennsylvania salary details

$23.6K

$37.8K

$51.1K

How much do databricks jobs pay per year?

As of Aug 23, 2026, the average yearly pay for databricks in Pennsylvania is $37,804.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,600.00 and $41,600.00 per year, depending on experience, location, and employer.

What is a Databricks?

A Databricks job is a way to run an automated workload, such as a data pipeline, machine learning model training, or ETL task, on the Databricks platform. Jobs can be scheduled, triggered manually, or run as part of a workflow. They support different task types, including notebooks, Python scripts, JARs, and SQL queries. Databricks jobs also allow for dependency management and orchestration across multiple tasks within a workflow.

What are the typical daily responsibilities of someone working in a Databricks role?

Professionals in Databricks roles typically spend their days developing and maintaining data pipelines, analyzing large datasets, and collaborating with business stakeholders to translate requirements into scalable solutions. They often use tools such as Apache Spark and cloud platforms to design and optimize workflows, while troubleshooting data quality or performance issues that arise. Regular teamwork with data engineers, analysts, and software developers is common, as is participating in sprint planning or code review sessions. Overall, the role combines hands-on technical work with ongoing collaboration to ensure data-driven insights and infrastructure reliability.

What are the key skills and qualifications needed to thrive in the Databricks position, and why are they important?

To thrive in a Databricks role, you need strong programming skills in languages such as Python or Scala, a deep understanding of data engineering or data science principles, and typically a relevant degree in computer science or a related field. Experience with Apache Spark, cloud platforms like Azure or AWS, and Databricks-specific certifications are often highly valued. Exceptional problem-solving, communication, and collaboration skills help professionals excel within multidisciplinary data teams. These capabilities are crucial for successfully designing, developing, and optimizing large-scale data solutions in a fast-evolving analytics environment.

Are Databricks in high demand?

Databricks-related roles, such as data engineers and data scientists, are in high demand due to the platform's widespread adoption for big data analytics and machine learning. Skills in Spark, cloud environments, and data pipeline development increase employability in this field.

Does Databricks hire remote employees?

Databricks offers remote work opportunities for certain roles, especially those related to software engineering, data science, and cloud infrastructure. The availability of remote positions depends on the specific job and team requirements, and candidates should review individual job postings for location details.

Is Databricks a good company to work for?

As a company, Databricks is known for its focus on data analytics and cloud-based platforms, offering roles that involve working with tools like Apache Spark and machine learning. Employee reviews often cite a collaborative environment and opportunities for skill development, though experiences can vary by role and location.

What are jobs in Databricks?

Jobs in Databricks refer to roles that involve developing, managing, and optimizing data workflows using the Databricks platform, which is built on Apache Spark. These positions often require skills in data engineering, data science, or machine learning, and may involve working with cloud environments, SQL, and programming languages like Python or Scala.

What are the most commonly searched types of Databricks jobs in Pennsylvania?

The most popular types of Databricks jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Databricks jobs?

Cities in Pennsylvania with the most Databricks job openings:

Infographic showing various Databricks job openings in Pennsylvania as of August 2026, with employment types broken down into 86% Full Time, 9% Part Time, and 5% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $37,804 per year, or $18.2 per hour.

Data Engineer - Databricks, AWS, Python

Computer Enterprises, Inc.

Philadelphia, PA • On-site

$115K - $138K/yr

Other

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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