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Databricks Developer Jobs in Columbus, OH (NOW HIRING)

Deloitte

Azure/Databricks Infrastructure Engineer

Columbus, OH · On-site

$53.75 - $72/hr

... DevOps or GitHub Actions * Supporting cloud modernization, analytics, AI, and enterprise data ... As an Azure/Databricks Infrastructure Engineer, you will design, implement, and optimize secure ...

McKesson Corporation

Data Architect, Databricks

Columbus, OH · On-site

$61.50 - $79.25/hr

You will partner closely with engineering, analytics, governance, and business teams to deliver ... Our team is early in its Databricks maturity journey, and this hire will establish foundational ...

McKesson

Data Architect, Databricks

Columbus, OH · On-site +1

$61.50 - $79.25/hr

You will partner closely with engineering, analytics, governance, and business teams to deliver ... Our team is early in its Databricks maturity journey, and this hire will establish foundational ...

McKesson

Data Architect, Databricks

Columbus, OH · On-site +1

$61.50 - $79.25/hr

You will partner closely with engineering, analytics, governance, and business teams to deliver ... Our team is early in its Databricks maturity journey, and this hire will establish foundational ...

SwiftCruit

Sr Data Architect, Databricks

Columbus, OH · On-site

$124.10 - $206.90/hr

Senior Data Architect (Databricks) This role will architect, standardize, and accelerate adoption ... You will partner closely with engineering, analytics, governance, and business teams to deliver ...

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Databricks Developer information

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How much do databricks developer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for databricks developer in Columbus, OH is $59.41, according to ZipRecruiter salary data. Most workers in this role earn between $53.41 and $65.72 per hour, depending on experience, location, and employer.

What are the typical daily responsibilities of a Databricks developer?

As a Databricks Developer, your typical day involves designing, developing, and maintaining scalable data pipelines using Databricks and Apache Spark. You’ll collaborate with data engineers, data scientists, and business analysts to ensure data is clean, accessible, and reliable for analytics and reporting. Tasks often include code reviews, optimizing data workflows, troubleshooting performance issues, and implementing best practices for data security and governance. This role offers a dynamic work environment that blends technical challenge with teamwork across multiple departments.

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

To thrive as a Databricks Developer, you need strong skills in data engineering, Spark programming, SQL, and cloud platforms, typically with a background in computer science or a related field. Hands-on experience with Databricks, Apache Spark, Python/Scala, and knowledge of cloud services like AWS or Azure, as well as relevant certifications, are highly valued. Analytical thinking, problem-solving, effective communication, and the ability to collaborate across teams are essential soft skills for this role. These abilities are crucial to designing scalable data solutions, streamlining data pipelines, and supporting business analytics in modern data-driven organizations.

What do you need to be a Databricks developer?

To become a Databricks developer, you typically need proficiency in Apache Spark, programming skills in languages like Python, Scala, or SQL, and experience with cloud platforms such as AWS or Azure. Knowledge of data engineering, ETL processes, and familiarity with Databricks' environment and tools are also important, along with relevant certifications or training.

What is a Databricks developer?

A Databricks Developer is responsible for designing, developing, and optimizing data pipelines and workflows using Databricks, a cloud-based data analytics platform. They work with big data technologies, such as Apache Spark, to process, transform, and analyze large datasets efficiently. Their role includes writing scalable code, creating data models, and collaborating with data engineers and analysts to support business intelligence and machine learning initiatives.

What is the salary of a Databricks developer?

The salary of a Databricks developer typically ranges from $90,000 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.

Is a Databricks developer an in demand skill?

Yes, Databricks developers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. Skills in Apache Spark, SQL, and cloud environments like AWS or Azure enhance employability in this role, which is often required in data-driven industries.
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Databricks Developer jobs near you
Infographic showing various Databricks Developer job openings in Columbus, OH as of August 2026, with employment types broken down into 79% Full Time, 3% Part Time, and 18% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $123,564 per year, or $59.4 per hour.

MLOps Engineer (Databricks/AWS)

Inabia Solutions and Consulting, Inc.

Columbus, OH • On-site

Contractor

Posted 20 days ago

Job description

Overview
Inabia is seeking an MLOps Engineer (Databricks/AWS) to design, develop, and maintain end-to-end machine learning operations pipelines on Databricks running on AWS. This role demands deep hands-on expertise with Databricks Machine Learning, MLflow, and a broad suite of AWS services to build scalable, production-grade ML systems. The ideal candidate will partner closely with Data Scientists, Data Engineers, and Platform Engineering teams to productionize models and ensure robust, governed, and cost-efficient deployments.
Locations: Columbus, OH - Dallas, TX - Atlanta, GA (Onsite only)
Responsibilities
  • Design, develop, and maintain end-to-end MLOps pipelines on Databricks running on AWS.
  • Build and automate machine learning workflows covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring.
  • Deploy and manage ML models using MLflow Model Registry and Databricks Model Serving.
  • Develop and maintain CI/CD pipelines for ML solutions across development, staging, and production environments.
  • Collaborate with Data Scientists to productionize machine learning models and ensure reliable, repeatable deployments.
  • Monitor model health, prediction quality, data drift, and system performance, and implement automated retraining strategies where required.
  • Optimize Databricks workloads for performance, scalability, and cost efficiency.
  • Implement Infrastructure as Code using Terraform to provision and manage Databricks and AWS resources.
  • Ensure platform security, governance, and compliance using Unity Catalog and AWS IAM.
  • Troubleshoot production issues, perform root cause analysis, and continuously improve platform reliability.
  • Document MLOps processes, deployment standards, and operational best practices.

Key Qualifications
  • 10+ years of relevant experience in MLOps or a closely related data/ML engineering discipline.
  • Strong hands-on experience with Databricks Machine Learning.
  • Proficiency in Python, PySpark, and SQL for developing and operationalizing machine learning solutions.
  • Hands-on experience with MLflow for experiment tracking, model registry, model versioning, and lifecycle management.
  • Experience deploying and managing machine learning models using Databricks Model Serving and batch inference pipelines.
  • Strong understanding of the end-to-end ML lifecycle, including feature engineering, training, validation, deployment, monitoring, and retraining.
  • Experience building scalable ML pipelines using Databricks Workflows and Delta Lake.
  • Hands-on experience with AWS services including S3, IAM, EC2, Lambda, ECR, ECS/EKS, CloudWatch, and Secrets Manager.
  • Experience implementing CI/CD pipelines for Databricks and ML workloads using Git, Bitbucket, Jenkins, and Databricks Asset Bundles (DAB).
  • Experience with infrastructure automation using Terraform.
  • Strong understanding of Apache Spark architecture, optimization, and distributed data processing.
  • Experience working with Unity Catalog for governance, security, and access management.
  • Knowledge of model monitoring, data drift detection, and automated retraining strategies.
  • Understanding of MLOps best practices including reproducibility, versioning, testing, and governance.
  • Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications
  • Experience with multi-environment Databricks deployments spanning development, staging, and production.
  • Familiarity with cost optimization strategies for large-scale Databricks and AWS workloads.
  • Prior experience documenting MLOps operational standards for cross-functional teams.

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