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Databricks Engineer Jobs in Peoria, IL (NOW HIRING)

Data Engineer

Peoria, IL ยท On-site

$112K - $135K/yr

We are seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines ... Experience with Databricks. * Experience with Apache Kafka. * Hands-on experience with Apache ...

Collaborate with cross-functional teams such as IT and engineering to integrate data from various ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Databricks Engineer information

See Peoria, IL salary details

$58.4K

$109.5K

$199.2K

How much do databricks engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for databricks engineer in Peoria, IL is $109,537.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,000.00 and $130,000.00 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 Peoria, IL? For Databricks Engineer jobs in Peoria, IL, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Peoria, IL look for? The top searched job categories for Databricks Engineer jobs in Peoria, IL are:
What cities near Peoria, IL are hiring for Databricks Engineer jobs? Cities near Peoria, IL with the most Databricks Engineer job openings:
Infographic showing various Databricks Engineer job openings in Peoria, IL as of June 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $109,537 per year, or $52.7 per hour.
Data Engineer

$112K - $135K/yr

Full-time

Posted 14 days ago


Job description

We are seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms. The ideal candidate will have strong expertise in Python, SQL, Spark, ETL processes, and cloud technologies to support data-driven decision-making and advanced analytics.
Key Responsibilities
  • Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
  • Build and optimize data processing solutions using Python, SQL, and Apache Spark (PySpark).
  • Develop batch and real-time data ingestion pipelines.
  • Work with structured and unstructured datasets from multiple data sources.
  • Design and implement cloud-based data solutions using Azure, AWS, or GCP.
  • Develop and maintain data models, data lakes, and enterprise data warehouses.
  • Integrate data from APIs, databases, and streaming platforms.
  • Optimize data pipeline performance and ensure data quality.
  • Collaborate with Data Scientists, Business Analysts, and Software Engineers.
  • Implement CI/CD pipelines and DevOps best practices for data engineering.
  • Troubleshoot production issues and provide ongoing support.
  • Ensure compliance with data governance, security, and privacy standards.
Required Skills
  • 5+ years of experience as a Data Engineer.
  • Strong programming skills in Python.
  • Excellent SQL skills.
  • Hands-on experience with Apache Spark / PySpark.
  • Experience with ETL/ELT development.
  • Strong knowledge of Data Warehousing concepts.
  • Experience with Hadoop ecosystem (Hive, HDFS).
  • Experience with Databricks.
  • Experience with Apache Kafka.
  • Hands-on experience with Apache Airflow or similar workflow orchestration tools.
  • Experience working on Linux/Unix environments.
  • Knowledge of Git and CI/CD pipelines.
Cloud Skills
Experience with one or more of the following:
  • Microsoft Azure (ADF, ADLS, Synapse)
  • Amazon Web Services (AWS)
  • Google Cloud Platform (GCP)
Preferred Skills
  • Snowflake
  • Delta Lake
  • Docker
  • Kubernetes
  • Terraform
  • Scala or Java
  • Power BI or Tableau
  • REST APIs
  • Agile/Scrum methodology
  • Experience working with large-scale enterprise data platforms