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Databricks Software Jobs in McKinney, TX (NOW HIRING)

MAQ Software

Software Data Operations Engineer

Plano, TX · On-site

$107K - $128K/yr

Software Data Operations Engineer Plano (Dallas), Texas About MAQ Software MAQ Software enables ... Our team leveraged Azure Databricks for advanced data transformation, Azure Front Door for global ...

MAQ Software

Software Data Operations Engineer

Plano, TX · On-site

$107K - $128K/yr

Software Data Operations Engineer  Plano (Dallas), Texas About MAQ Software MAQ Software enables ... Our team leveraged Azure Databricks for advanced data transformation, Azure Front Door for global ...

Prophecy Technologies

Databricks Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

This role is for a skilled Data Engineer with extensive hands-on experience in Databricks, focusing on building and optimizing scalable data pipelines. The successful candidate will leverage advanced ...

Deloitte

Sr Databricks Data Engineer

Dallas, TX

$113K - $136K/yr

As a Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud-based data engineering solutions that support large-scale transformation. You will work with business ...

KPMG

Manager, Data Engineer - Databricks

Dallas, TX · On-site

$113K - $136K/yr

KPMG is currently seeking a Manager, Data Engineer - Databricks for our Consulting practice. Responsibilities: * Assist with technical design and development activities and lead a small workstream ...

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All JobsDatabricks Software JobsDatabricks Software Jobs in McKinney, TX

Databricks Software information

See McKinney, TX salary details

$44.5K

$103.8K

$154.1K

How much do databricks software jobs pay per year?

As of Sep 3, 2026, the average yearly pay for databricks software in McKinney, TX is $103,796.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $120,600.00 per year, depending on experience, location, and employer.

What is Databricks software?

Databricks Software is a unified analytics platform built on Apache Spark that provides tools for big data processing, machine learning, and collaborative data science. It enables organizations to store, manage, and analyze large datasets efficiently, supporting both batch and streaming data workloads. Databricks also offers collaborative notebooks, automated workflows, and integrations with cloud storage and data lakes, making it a popular choice for data engineering, data science, and business analytics teams.

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

To thrive as a Databricks Software Engineer, you need strong programming skills in languages like Python, Scala, or Java, as well as a solid understanding of distributed computing and data engineering concepts. Familiarity with Databricks platform, Apache Spark, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valued. Excellent problem-solving abilities, collaboration, and effective communication are important soft skills for this role. These skills ensure efficient development, deployment, and optimization of big data solutions that drive business insights and innovation.

What are some common challenges faced by Databricks software engineers, and how can they be overcome?

Databricks Software Engineers often encounter challenges related to scaling big data pipelines, optimizing Spark workloads, and integrating diverse data sources. Navigating the complexity of distributed systems and managing cloud infrastructure can be demanding, especially when ensuring data reliability and security. To overcome these challenges, engineers typically collaborate closely with data scientists, DevOps, and platform teams, leverage Databricks' extensive documentation and community support, and adopt best practices such as version control and continuous integration. Regular knowledge sharing and staying updated with new features also help engineers succeed in this dynamic environment.

What is the difference between Databricks Software vs Data Engineer?

AspectDatabricks SoftwareData Engineer
Primary RolePlatform for data analytics and machine learningBuilds, maintains data pipelines and infrastructure
Required SkillsSQL, Spark, cloud platforms, data science basicsSQL, ETL, programming (Python, Scala), database management
Work EnvironmentCloud-based, collaborative data platformData teams, cloud or on-premises environments
CertificationsDatabricks certifications, cloud certificationsNone specific, often cloud or data certifications

While Databricks Software provides a platform for data analytics and machine learning, Data Engineers focus on building and maintaining data pipelines and infrastructure. Both roles often work together but have distinct responsibilities and skill sets within the data ecosystem.

What are popular job titles related to Databricks Software jobs in McKinney, TX?

For Databricks Software jobs in McKinney, TX, the most frequently searched job titles are:

What job categories do people searching Databricks Software jobs in McKinney, TX look for?

The top searched job categories for Databricks Software jobs in McKinney, TX are:

What cities near McKinney, TX are hiring for Databricks Software jobs?

Cities near McKinney, TX with the most Databricks Software job openings:

Databricks Software jobs near you
Infographic showing various Databricks Software job openings in McKinney, TX as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $103,796 per year, or $49.9 per hour.

Sr. Forward Deployed Engineer (FDE) - Financial Services

Databricks

Dallas, TX

$103K - $142K/yr

Full-time

Re-posted 12 days ago

Job description

CSQ327R59

As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. 

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

The impact you will have:

  • Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
  • Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
  • Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  • Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
  • Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
  • Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
  • Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

  • 6+ years experience in data engineering, data platforms & analytics, or software engineering
  • Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
  • Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
  • Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals
  • Familiarity with CI/CD for production deployments
  • Working knowledge of MLOps, ML/AI models and AI APIs
  • Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
  • Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
  • Documentation and white-boarding skills.
  • Experience working with enterprise clients and managing conflicts across a broad stakeholder range
  • Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
  • Travel to customers 20% of the time
  • Databricks Certification

Apply