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Databricks Engineer Jobs in Delaware (NOW HIRING)

Dlapiper

Data Engineer

Wilmington, DE · On-site

$111K - $133K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Judge Group, Inc.

Data Engineer

Wilmington, DE · On-site

$80 - $85/hr

Role: Senior Data Engineer Duration: 6-12+ months RTH Location: Wilmington, Delaware Interview ... Databricks), Airflow, Relational Databases Nice to Haves: Snowflake, NoSql Databases TDD, CI/CD ...

Judge Group, Inc.

Sr. Data Engineer

Wilmington, DE · On-site

$102K - $139K/yr

Our client is seeking an experienced Senior Data Engineer to join their growing data team. This is ... Experience working with Apache Spark and Databricks * Proficiency in workflow orchestration tools ...

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Databricks Engineer information

See Delaware salary details

$59.6K

$111.7K

$203.2K

How much do databricks engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for databricks engineer in Delaware is $111,728.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,600.00 and $132,600.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

What are the key skills and qualifications needed to thrive as a Databricks Engineer, and why are they important?

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
What are popular job titles related to Databricks Engineer jobs in Delaware? For Databricks Engineer jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Delaware look for? The top searched job categories for Databricks Engineer jobs in Delaware are:
What cities in Delaware are hiring for Databricks Engineer jobs? Cities in Delaware with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Delaware as of July 2026, with employment types broken down into 1% As Needed, 89% Full Time, 5% Part Time, and 5% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $111,728 per year, or $53.7 per hour.

AWS Databricks Engineer

R2 Technologies Corporation

Wilmington, DE • On-site

Full-time

Re-posted 6 days ago

Job description

Overview:
AWS Databricks Engineer -12+yrs- Wilmington, DE (Day 1 Onsite)
Job Description
• 12+ years of overall experience in data engineering, cloud architecture, or analytics platforms.
• Strong expertise in AWS big-data stack and Databricks Lakehouse.
• Hands-on experience building enterprise-grade data platforms and multi-zone Lakehouse architectures.
Deep knowledge of:
o Spark optimization
o Delta Lake internals
o Data quality & observability
• Strong understanding of zero-trust security, compliance, an

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