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Databricks Jobs in Texas (NOW HIRING)

Tangentia

Databricks Technical Architect

Dallas, TX · On-site

Position Overview We are seeking a Databricks Architect to lead the data and analytics architecture supporting Finance processes across the enterprise. This role will bridge Finance business ...

McKesson

Data Architect, Databricks

Irving, TX · On-site +1

$61.25 - $78.75/hr

Our team is early in its Databricks maturity journey, and this hire will establish foundational standards, processes, and scaling capabilities across the platform . * Our preferred candidate would ...

Balin Technologies LLC

Sr Azure DataBricks Engineer

Dallas, TX · On-site

$103K - $142K/yr

Dallas,TX(Onsite) OVERALL EXPEREINCE 10YRS+ Prepare the Databricks Serverless environment for the team Set up job clusters Ensure all libraries needed are present Work with Databricks and CDO to ...

dhanutek

Databricks Developer - Python & Scala

Dallas, TX · On-site

$49.75 - $68.50/hr

Databricks Developer - Python & Scala Location: Dallas, TX - onsite Duration: 12+ Months with possible extension Experience: 7+ years We are looking for an experienced Databricks Developer with ...

McKesson

Data Architect, Databricks

Irving, TX · On-site +1

$61.25 - $78.75/hr

Our team is early in its Databricks maturity journey, and this hire will establish foundational standards, processes, and scaling capabilities across the platform . * Our preferred candidate would ...

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How much do databricks jobs pay per year?

As of Sep 9, 2026, the average yearly pay for databricks in Texas is $35,136.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,200.00 and $38,700.00 per year, depending on experience, location, and employer.

What is a Databricks?

A Databricks job is a way to run an automated workload, such as a data pipeline, machine learning model training, or ETL task, on the Databricks platform. Jobs can be scheduled, triggered manually, or run as part of a workflow. They support different task types, including notebooks, Python scripts, JARs, and SQL queries. Databricks jobs also allow for dependency management and orchestration across multiple tasks within a workflow.

What are the typical daily responsibilities of someone working in a Databricks role?

Professionals in Databricks roles typically spend their days developing and maintaining data pipelines, analyzing large datasets, and collaborating with business stakeholders to translate requirements into scalable solutions. They often use tools such as Apache Spark and cloud platforms to design and optimize workflows, while troubleshooting data quality or performance issues that arise. Regular teamwork with data engineers, analysts, and software developers is common, as is participating in sprint planning or code review sessions. Overall, the role combines hands-on technical work with ongoing collaboration to ensure data-driven insights and infrastructure reliability.

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

To thrive in a Databricks role, you need strong programming skills in languages such as Python or Scala, a deep understanding of data engineering or data science principles, and typically a relevant degree in computer science or a related field. Experience with Apache Spark, cloud platforms like Azure or AWS, and Databricks-specific certifications are often highly valued. Exceptional problem-solving, communication, and collaboration skills help professionals excel within multidisciplinary data teams. These capabilities are crucial for successfully designing, developing, and optimizing large-scale data solutions in a fast-evolving analytics environment.

Are Databricks in high demand?

Databricks-related roles, such as data engineers and data scientists, are in high demand due to the platform's widespread adoption for big data analytics and machine learning. Skills in Spark, cloud environments, and data pipeline development increase employability in this field.

Does Databricks hire remote employees?

Databricks offers remote work opportunities for certain roles, especially those related to software engineering, data science, and cloud infrastructure. The availability of remote positions depends on the specific job and team requirements, and candidates should review individual job postings for location details.

Is Databricks a good company to work for?

As a company, Databricks is known for its focus on data analytics and cloud-based platforms, offering roles that involve working with tools like Apache Spark and machine learning. Employee reviews often cite a collaborative environment and opportunities for skill development, though experiences can vary by role and location.

What are jobs in Databricks?

Jobs in Databricks refer to roles that involve developing, managing, and optimizing data workflows using the Databricks platform, which is built on Apache Spark. These positions often require skills in data engineering, data science, or machine learning, and may involve working with cloud environments, SQL, and programming languages like Python or Scala.

What are the most commonly searched types of Databricks jobs in Texas?

The most popular types of Databricks jobs in Texas are:

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For Databricks jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Databricks jobs in Texas look for?

The top searched job categories for Databricks jobs in Texas are:

What cities in Texas are hiring for Databricks jobs?

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Databricks jobs near you
Infographic showing various Databricks job openings in Texas as of September 2026, with employment types broken down into 45% Full Time, 5% Part Time, and 50% Contract. Highlights an 90% In-person, 5% Hybrid, and 5% Remote job distribution, with an average salary of $35,136 per year, or $16.9 per hour.

Databricks Technical Architect

Dallas, TX • On-site

Tangentia
See more jobs at Tangentiaexternal

Full-time

Posted 12 days ago

Job description

Position Overview
We are seeking a Databricks Architect to lead the data and analytics architecture supporting Finance processes across the enterprise.
This role will bridge Finance business processes, SAP/ERP data, Databricks, enterprise data architecture, and AI/analytics. The architect will work closely with Finance process owners, data engineers, integration architects, enterprise architects, and technology teams to define and implement a scalable data foundation for Financial Shared Services. The ideal candidate combines strong Databricks and modern data platform expertise with a solid understanding of Finance processes, SAP financial data, data governance, and enterprise integration.
Key Responsibilities
Financial Shared Services Data Strategy
  • Partner with Finance Shared Services leadership and process owners to understand business processes, pain points, KPIs, and data requirements.
  • Translate Finance business requirements into comprehensive data architecture and roadmap.
  • Define data products and analytical capabilities supporting areas such as:
    • Accounts Payable
    • Accounts Receivable
    • General Ledger
    • Record-to-Report
    • Procure-to-Pay
    • Order-to-Cash
    • Fixed Assets
    • Intercompany Accounting
    • Cash Management
    • Financial Close
    • Working Capital
  • Identify opportunities to use data, analytics, automation, and AI to improve Finance Shared Services efficiency and decision-making.
Databricks Architecture
  • Define and lead the implementation of scalable Databricks Lakehouse architecture supporting Finance data and analytics.
  • Establish architecture patterns for ingestion, transformation, storage, data products, semantic models, and consumption.
  • Design Bronze/Silver/Gold data layers and establish standards for financial data processing.
  • Define approaches for batch and near-real-time data processing.
  • Establish reusable patterns for data quality, lineage, metadata, security, and governance.
  • Optimize Databricks workloads for scalability, performance, reliability, and cost.
SAP and Enterprise Data Integration
  • Architect integration of SAP ECC and other enterprise applications with Databricks.
  • Understand SAP Finance data structures, including financial accounting, controlling, procurement, assets, and related master data.
  • Define authoritative sources and data ownership for financial information.
  • Work with integration teams to establish appropriate patterns using APIs, events, replication, files, and other integration mechanisms.
  • Ensure financial data remains consistent across SAP, Databricks, reporting platforms, and downstream applications.
Data Products & Analytics
  • Lead the creation of governed Finance data products that can support reporting, analytics, forecasting, automation, and AI use cases.
  • Define business and technical metadata for critical financial data.
  • Establish common definitions for Finance KPIs and metrics.
  • Enable self-service analytics while maintaining appropriate governance and controls.
  • Support development of advanced analytics and AI capabilities using trusted financial data.
Data Governance & Controls
  • Establish data governance standards appropriate for financial data.
  • Define data ownership, stewardship, lineage, quality rules, retention, and access controls.
  • Ensure architecture supports financial controls, auditability, traceability, and regulatory requirements.
  • Implement appropriate security and access models for sensitive financial information.
  • Partner with Finance data owners to establish data quality and reconciliation processes.
Architecture Leadership
  • Serve as the primary technical architecture lead for Finance Shared Services data initiatives.
  • Develop target-state architecture, solution architecture, integration patterns, and technical roadmaps.
  • Review solution designs and ensure adherence to enterprise architecture standards.
  • Guide engineering teams and provide technical leadership throughout implementation.
  • Evaluate new Databricks, cloud, AI, and data technologies for applicability to Finance.
  • Drive architecture decisions across business, data, application, integration, and technology domains.
Required Qualifications
  • Bachelor's degree in Computer Science, Information Systems, Engineering, Finance, or a related field.
  • 8+ years of experience in data architecture, data engineering, enterprise architecture, or related technology roles.
  • Strong hands-on architecture experience with Databricks and modern cloud data platforms.
  • Strong understanding of Lakehouse architecture, Delta Lake, Spark, SQL, and data engineering patterns.
  • Experience designing enterprise-scale data platforms and data products.
  • Strong understanding of SAP data, preferably SAP S/4HANA Finance.
  • Experience integrating SAP and non-SAP enterprise applications with modern data platforms.
  • Strong understanding of data governance, security, metadata, lineage, and data quality.
  • Experience working directly with Finance or Financial Shared Services organizations.
  • Ability to translate complex business requirements into scalable technical architecture.
Preferred Qualifications
  • Databricks certifications such as Databricks Certified Data Engineer or Data Architect.
  • Experience with SAP Finance Processes
  • Experience with SAP data replication or integration technologies.
  • Experience with Azure, AWS, or GCP.
  • Experience with enterprise event-driven architecture and APIs.
  • Experience with Power BI or other enterprise analytics platforms.
  • Experience implementing AI/ML or GenAI solutions using enterprise data.
  • Experience with data mesh, data products, or domain-oriented data architecture.
  • Experience supporting financial close, reconciliation, controls, and audit requirements.
  • Experience working in large global enterprises with complex Finance organizations.
Key Competencies
  • Finance Process Understanding
  • Databricks & Lakehouse Architecture
  • SAP Finance Data
  • Enterprise Data Architecture
  • Data Governance
  • Cloud & Integration Architecture
  • Data Products & Analytics
  • AI/ML & GenAI Enablement
  • Stakeholder Management
  • Architecture Leadership
Success Measures
Success in this role will be measured by the ability to:
  • Establish a scalable and governed Finance data foundation on Databricks.
  • Reduce complexity and duplication across Finance data sources.
  • Create trusted, reusable Finance data products.
  • Improve data quality, reconciliation, and transparency across Financial Shared Services.
  • Enable faster delivery of Finance analytics, automation, and AI use cases.
  • Establish clear ownership and governance of critical financial data.
  • Successfully translate Finance business priorities into an executable technology roadmap.
  • Deliver measurable improvements in Finance Shared Services efficiency and decision-making.

Role Profile
This is an architecture leadership role requiring an individual who can operate comfortably at the intersection of Finance, SAP, Databricks, enterprise architecture, data engineering, and AI.
The successful candidate should be able to move from "What Finance process are we trying to improve?" → "What data is required?" → "Where does that data originate?" → "How should it be integrated and governed?" → "How should it be modeled in Databricks?" → "What analytics/automation/AI capability can we enable?"
The role is therefore suited to a senior/principal-level Data Architect or Databricks Architect rather than a purely hands-on Databricks engineer.

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