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Databricks Engineer Jobs in Cleveland, OH (NOW HIRING)

Nestle

Senior Supply Chain Analytics Analyst

Solon, OH

$105K - $120K/yr

... Databricks Genie) to enable self-service reporting, automated insights, and intelligent analytics ... Mathematics, Statistics, Engineering, or a related discipline Plus, a minimum of 1 year of ...

Eisneramper Llp

AI Solution Architect

Cleveland, OH · On-site +1

$61 - $80.50/hr

Azure Databricks: Data engineering and ML model development * Programming Languages: Python, C#, JavaScript/TypeScript, SQL * AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Transformers

Pwc

AI & GenAI Data Scientist - Manager

Cleveland, OH · On-site

$99K - $232K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

Deloitte

Senior Manager Data Lead

Cleveland, OH · On-site

Join our AI & Engineering team in transforming technology platforms, driving innovation, and ... Snowflake, Databricks, BigQuery, Teradata) * ETL/ELT tools and data integration patterns within ...

Pwc

Data Strategy-Manager

Cleveland, OH

$99K - $232K/yr

... Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in defining data governance frameworks - Understanding of modern cloud data ...

Pwc

Data Strategy & Governance -Director

Cleveland, OH

$155K - $410K/yr

... Databricks Certified Data Engineer/Data Analyst/ML - Proven leadership in data-driven strategies - Demonstrating thought leadership in data governance - Collaborating on strategy and transformation ...

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All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Cleveland, OH

Databricks Engineer information

See Cleveland, OH salary details

$57.6K

$108.1K

$196.6K

How much do databricks engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for databricks engineer in Cleveland, OH is $108,099.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,000.00 and $128,300.00 per year, depending on experience, location, and employer.

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?

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 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 $90,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, and data engineering can earn higher compensation, often including bonuses and benefits.

Is a Databricks engineer in demand?

Databricks engineers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. They typically require skills in Spark, SQL, and cloud environments like AWS or Azure, making them valuable in data-driven organizations across various industries.

What are popular job titles related to Databricks Engineer jobs in Cleveland, OH?

For Databricks Engineer jobs in Cleveland, OH, the most frequently searched job titles are:

What job categories do people searching Databricks Engineer jobs in Cleveland, OH look for?

The top searched job categories for Databricks Engineer jobs in Cleveland, OH are:

What cities near Cleveland, OH are hiring for Databricks Engineer jobs?

Cities near Cleveland, OH with the most Databricks Engineer job openings:

Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Cleveland, OH as of August 2026, with employment types broken down into 89% Full Time, 6% Part Time, and 5% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $108,099 per year, or $52 per hour.

Sr. Manager, Data Engineering

Park Place Technologies

Highland Heights, OH • On-site

Full-time

Re-posted 12 days ago

Park Place Technologies rating

7.8

Company rating: 7.8 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

88th of 226 rated it services

Job description

Sr. Manager, Data Engineering
The Sr. Manager, Data Engineering is a key senior leader responsible for the strategy, architecture, and execution of the enterprise data engineering function. This leader will build and scale a high-performing team, drive strategy and design of the data engineering framework for reporting needs, facilitates strategy around the data warehouse, partners with other IT leaders to provide availability of data for AI/ML initiatives, assists with business intelligence, and core operational systems for seamless reporting. Reporting to senior technology leadership, this role serves as a strategic partner to IT, Analytics, and business stakeholders to ensure data is reliable, governed [in partnership with master data management], and accessible at scale.
This is a high-impact opportunity for a technically grounded, people-first leader who thrives in a fast-paced environment and is energized by building scalable systems during a period of significant growth, including M&A integration and cloud transformation.
Responsibilities:
  • Leadership & Strategy
    • Define and drive the enterprise data engineering roadmap, aligned to business and technology goals
    • Build, lead, and mentor a multi-disciplinary team of data engineers (10-15) and product owner(s) (1-2)
    • Partner with the CIO, Analytics, AI, and business leadership to prioritize and deliver data capabilities
    • Establish engineering standards, best practices, and an operational excellence framework across the data organization
    • Champion a culture of data quality, engineering rigor, and continuous improvement
  • Platform & Architecture
    • Architect and oversee scalable data pipelines, data lakes, warehouses, and real-time streaming infrastructure
    • Lead cloud-native data platform strategy and adoption across Azure, AWS, or GCP environments
    • Own the selection, implementation, and lifecycle management of data engineering tools and platforms
    • Ensure data platform reliability, performance, and cost efficiency at scale
    • Partner with Platform Development Architects and leadership on integration patterns across key enterprise systems, including ERP, ServiceNow, and supply chain platforms
  • Data Governance & Quality
    • Own and evolve the enterprise data governance framework, including data lineage, cataloging, and access controls
    • Define and enforce data quality standards, measurement, and remediation processes
    • Partner with Security and Legal to ensure compliance with data privacy regulations and policies
    • In partnership with the Director of Development and AI, drive adoption of clean, governed, AI-ready data as a core organizational asset.
  • Delivery & Operations
    • Manage team delivery across multiple concurrent programs, including integration workstreams from M&A activity
    • Lead data engineering support for AI/ML platform enablement
    • Oversee vendor relationships, contracts, and budget for data infrastructure and tooling
    • Establish SLAs, incident management, and monitoring for data platform operations

Basic Qualifications:
  • 10+ years of progressive experience in data engineering, data architecture, or a related technical discipline
  • 5+ years of people leadership experience, including managing and developing senior engineers and managers; Communication is a critical facet for this role with an ability to manage up, to the side or down.
  • Proven track record of architecting and delivering enterprise-scale data platforms in production
  • Deep expertise in modern data stack tooling (e.g., Azure SQL, Azure Fabric, Kafka, Snowflake, Databricks, or equivalents)
  • Strong cloud data platform experience on Azure, AWS, or GCP
  • Demonstrated experience in data governance programs and data quality frameworks
  • Ability to translate complex business requirements into pragmatic technical strategy and roadmaps
  • Strong executive communication skills; comfortable presenting to C-suite and board-level audiences
  • Experience operating in dynamic, growth-stage environments, including M&A integration preferred
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or related field; Master's preferred

Preferred Qualifications:
  • Experience in IT services, managed services, or enterprise technology industries
  • Familiarity with ERP, ServiceNow, or supply chain data ecosystems
  • Experience leading data strategy and integration through M&A events
  • Exposure to data mesh, data product, or federated governance models
  • Relevant certifications in cloud data platforms (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate)
  • A strategic mindset paired with a bias for action and hands-on delivery
  • Passion for building reliable, scalable, and well-governed data systems
  • A collaborative and inclusive leadership style with the ability to influence across levels
  • Intellectual curiosity and a continuous improvement mindset
  • High standards for data quality and a commitment to engineering excellence

Travel:
  • 15%

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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