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Remote Databricks Data Engineer Jobs in Ohio (NOW HIRING)

Riverside Research

Remote Sensing Scientist

Dayton, OH · Remote

$91K - $140K/yr

Experience with common remote sensing EO-IR data formats Desired Qualifications: * Master's degree in Electrical Engineering, Physics, or comparable technical degree * Experience working with ...

CareSource

Data Scientist III

Dayton, OH · On-site +1

$94K - $164K/yr

Minimum of five (5) years of experience in data analysis and/or analytic programming required * Experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or ...

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Remote Databricks Data Engineer information

What is a remote Databricks data engineer?

A Remote Databricks Data Engineer is a professional who designs, develops, and manages large-scale data processing systems using the Databricks platform, often working from a remote location. They focus on building data pipelines, integrating data sources, and optimizing workflows for analytics and machine learning, leveraging tools like Apache Spark within Databricks. These engineers collaborate with data scientists, analysts, and other stakeholders to ensure data is accessible, reliable, and scalable for business needs. Remote roles offer flexibility in work location while still requiring strong communication and technical skills.

What are the key skills and qualifications needed to thrive as a remote Databricks data engineer?

To thrive as a Remote Databricks Data Engineer, you need a solid background in data engineering, strong programming skills in Python or Scala, and experience with big data frameworks, often supported by a degree in computer science or a related field. Proficiency with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valuable. Strong problem-solving abilities, effective remote communication, and collaboration skills set top performers apart in distributed teams. These skills and qualities ensure efficient data pipeline development, seamless integration, and successful project delivery in remote environments.

What are some common challenges faced by remote Databricks data engineers and how can they be addressed?

Remote Databricks Data Engineers often encounter challenges such as coordinating efficiently with distributed teams, managing access to secure data environments, and ensuring smooth pipeline deployments across different cloud platforms. To overcome these, it's important to leverage communication tools for regular check-ins, follow strict data governance protocols, and utilize collaborative features in Databricks such as shared notebooks and version control. Proactively documenting your work and staying updated with platform updates can also help streamline remote collaboration and problem-solving.

What are the most commonly searched types of Databricks Data Engineer jobs in Ohio?

The most popular types of Databricks Data Engineer jobs in Ohio are:

What are popular job titles related to Remote Databricks Data Engineer jobs in Ohio?

For Remote Databricks Data Engineer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Remote Databricks Data Engineer jobs in Ohio look for?

The top searched job categories for Remote Databricks Data Engineer jobs in Ohio are:

What cities in Ohio are hiring for Remote Databricks Data Engineer jobs?

Cities in Ohio with the most Remote Databricks Data Engineer job openings:

Remote Databricks Data Engineer jobs near you
Infographic showing various Remote Databricks Data Engineer job openings in Ohio as of September 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 100% Remote job distribution.

Data Ontology & Standards Engineer/Scientist

Dayton, OH • On-site, Remote

Apogee Engineering, LLC
See more jobs at Apogee Engineering, LLCexternal

Full-time

Posted 22 days ago

Job description

Overview

Apogee is seeking a Data Ontology & Standards Engineer/Scientist to Lead the design and governance of mission-focused data ontologies, standards, and knowledge models to enable interoperable, integrated intelligence data across NASIC and partner enterprises.

****Contingent Upon Contract Award****

Responsibilities
  • Develop and maintain knowledge models, including mission-relevant terms, definitions, hierarchies, and relationships.
  • Define and document data standards that enable consistent data integration and reuse.
  • Collaborate with cross-functional teams (mission analysts, engineers, architects, data owners) to validate and adopt standards.
  • Guide data architecture planning and standard approval processes in coordination with governance bodies.
  • Support integration of ontologies and standards into tools, repositories, and workflows.
  • Produce the monthly Data Ontology Posture Report documenting progress against mission requirements and recommended standards.
Qualifications

Minimum Experience:

Citizenship: Must be a US citizen Clearance: Ability to obtain and maintain TS/SCIEducation / Years of Experience:

  • Bachelor's degree in Information Science, Computer Science, Data Science, or related field.
  • 8+ years of experience in data architecture, ontology/metadata design, or enterprise data management.
  • Experience defining and managing controlled vocabularies, taxonomies, or ontologies in complex domains.
  • Strong understanding of data modeling concepts and data integration patterns.
  • Demonstrated ability to lead cross-functional standards and governance efforts.

Preferred Qualifications:

  • Experience with semantic technologies (e.g., RDF/OWL, knowledge graphs) or standards such as UML, OWL, or SKOS.
  • Background in intelligence data standards or community data models.
  • Experience implementing data standards within cloud or enterprise platforms.
  • Familiarity with MBSE, digital engineering, or analytics platforms that consume standard data models.

Additional InformationLocation:  Wright Patterson AFB Dayton, OHOn-site/Hybrid/Remote: On-siteTravel: Occassional

Employment Type: FULL_TIME

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