ZipRecruiter

Log In

1

Databricks Engineer Jobs in Texas (NOW HIRING)

next page

Showing results 1-20

All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Texas

Databricks Engineer information

See Texas salary details

$55.4K

$104K

$189.1K

How much do databricks engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for databricks engineer in Texas is $104,002.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $123,400.00 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 Texas? For Databricks Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Texas look for? The top searched job categories for Databricks Engineer jobs in Texas are:
What cities in Texas are hiring for Databricks Engineer jobs? Cities in Texas with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Data & AI Automation Engineer (Databricks)

Data & AI Automation Engineer (Databricks)

IT America Inc

Austin, TX • On-site

Contractor

Re-posted 4 days ago

Job description

Position: Data & AI Automation Engineer (Databricks)

Location: Austin, TX (Locals preferred - Hybrid 3 Days Onsite Weekly)

Duration: Long-Term Contract

Required Skills: Azure Databricks, Azure Cloud, Generative AI, LLMs

Note: Looking for Permanent / Visa Independent Consultants

Overview:

We are seeking an experienced Data & AI Automation Engineer to lead the development of intelligent automation solutions within an Azure Databricks ecosystem. This role focuses on leveraging Large Language Models (LLMs), AI agents, and advanced automation techniques to enhance data engineering productivity, accelerate software delivery, and improve data quality processes.

The ideal candidate will combine strong data engineering expertise with AI-driven automation capabilities to build scalable solutions that streamline development, testing, governance, and operational activities across the data platform. Working closely with architects, engineers, and platform teams, this individual will help drive innovation through intelligent agent frameworks and automated workflows.

Key Responsibilities:

  • Architect and develop AI-powered agents using LLMs, rule-based logic, or hybrid approaches to automate data engineering operations within Azure Databricks.
  • Create automation solutions that generate, optimize, and refactor PySpark and SQL code to improve development efficiency and maintainability.
  • Design intelligent testing and validation agents to automate data quality assessments, reconciliation processes, and QA activities.
  • Implement automated governance capabilities including metadata management, lineage tracking, compliance monitoring, and policy enforcement.
  • Develop autonomous CI/CD functions such as test creation, deployment verification, release validation, and recovery/rollback procedures.
  • Build monitoring and diagnostic agents capable of detecting anomalies, identifying performance issues, and supporting root-cause investigations.
  • Establish prompt engineering standards, reusable templates, and agent orchestration patterns tailored to enterprise data platforms.
  • Partner with data engineering and architecture teams to identify automation opportunities and prioritize high-value initiatives.
  • Define and enforce best practices for AI agent lifecycle management, including development, testing, deployment, observability, and maintenance.
  • Produce technical documentation, workflow diagrams, operational procedures, and knowledge-transfer materials.
  • Evaluate emerging AI technologies, agent frameworks, and automation tools to support continuous platform improvement.

Required Experience:

  • 10+ years of experience in Data Engineering, Software Engineering, or a related technical discipline.
  • Extensive hands-on experience with modern cloud data platforms such as Azure Databricks, Snowflake, or similar technologies.
  • Proven background building AI-driven automation solutions utilizing LLMs, prompt engineering methodologies, and agent orchestration frameworks.
  • Strong programming expertise in Python and advanced SQL development within production environments.
  • Practical experience working with Azure Databricks, including notebooks, workflows, jobs, Delta Live Tables (DLT), and related services.
  • Experience implementing CI/CD and Continuous Testing (CT) pipelines using tools such as GitHub Actions and Azure DevOps.
  • Demonstrated success creating automated testing frameworks, data validation solutions, or quality assurance processes.
  • Previous experience supporting highly regulated, compliance-driven, or risk-sensitive environments is advantageous.

Technical Skills:

  • Advanced Python development skills with a strong foundation in software engineering principles, testing methodologies, documentation standards, and source control practices.
  • Expertise in SQL and PySpark performance tuning and optimization.
  • Hands-on experience integrating LLM services, AI APIs, prompt engineering techniques, and agent frameworks such as Databricks Agent Framework, LangChain, AutoGen, OpenAI, or Azure OpenAI.
  • Deep understanding of Azure Databricks, including Delta Lake, workflows, asset bundles, and enterprise-scale data processing.
  • Experience building workflow automation solutions using orchestration platforms, serverless technologies, or event-driven architectures.
  • Strong analytical skills with the ability to break down complex business and technical processes into scalable automation components.
  • Excellent communication skills with the ability to explain technical designs, AI agent architectures, and automation strategies to both technical and non-technical stakeholders.

Education:

  • Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related field.
  • Master’s degree preferred.