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Databricks Engineer Jobs in Allen, TX (NOW HIRING)

JPS Tech Solutions LLC

Databricks Admin

Dallas, TX · On-site

Strong understanding of data engineering needs Strong understanding of aws infrastructure required by Databricks Experience with compliance audits/audit documentation Experience using Databricks APIs ...

Noblesoft Technologies

Databricks Architect

Dallas, TX · Remote

$66.25 - $87/hr

Subject Matter Expert (SME) level experience in Cloud Engineering, specifically with Databricks, Azure Data Factory, Data Lake, Delta Lake, and UnityCatalog. * Proficiency in Python, Spark, and ...

Tiger Analytics Inc.

Databricks Admin

Dallas, TX · Remote

This role will provide technical solution to multiple engineering and operation teams, develop ... Requirements The Azure Databricks Administrator will be responsible for providing technical ...

Tiger Analytics Inc.

Databricks Admin

Dallas, TX · On-site +1

This role will provide technical solution to multiple engineering and operation teams, develop ... Requirements The Azure Databricks Administrator will be responsible for providing technical ...

Tiger Analytics Inc.

Databricks Admin

Dallas, TX

This role will provide technical solution to multiple engineering and operation teams, develop ... Requirements The Azure Databricks Administrator will be responsible for providing technical ...

ClifyX

Databricks Admin SME

Dallas, TX · On-site

The role involves administration, governance, performance optimization, and security implementation of the Databricks platform while supporting critical data engineering and analytics workloads.

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Databricks Engineer information

See Allen, TX salary details

$55.3K

$103.8K

$188.8K

How much do databricks engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for databricks engineer in Allen, TX is $103,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,900.00 and $123,200.00 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 $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 architecture can earn higher compensation, often exceeding $160,000 per year.

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, and their roles are often available across various industries seeking data-driven solutions.

What are popular job titles related to Databricks Engineer jobs in Allen, TX?

For Databricks Engineer jobs in Allen, TX, the most frequently searched job titles are:

What job categories do people searching Databricks Engineer jobs in Allen, TX look for?

The top searched job categories for Databricks Engineer jobs in Allen, TX are:

What cities near Allen, TX are hiring for Databricks Engineer jobs?

Cities near Allen, TX with the most Databricks Engineer job openings:

Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Allen, TX as of August 2026, with employment types broken down into 87% Full Time, 7% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $103,837 per year, or $49.9 per hour.

Lead Software Engineer - Databricks, ML, AWS

JPMorgan Chase & Co.

Plano, TX • On-site

Full-time

Medical, Retirement

Posted 24 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description


We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Lead Software Engineer, Machine Learning and Cloud at JPMorgan Chase within the Corporate Technology- Consumer & Community Bank Finance group, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor and lead, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job Responsibilities:
  • Lead architecture and delivery of high-throughput, low-latency data pipelines using Databricks and Apache Spark (Core, SQL, Structured Streaming).
  • Establish lakehouse patterns with Delta Lake (ACID transactions, schema evolution, time travel, Z-ordering, compaction) and ensure performance at scale.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Own Databricks cluster strategy and setup: runtime selection, autoscaling, driver/executor sizing, Spark configs, unit scripts, cluster policies, pools, and instance profiles.
  • Orchestrate jobs with Databricks Workflows; integrate with AWS eventing and orchestration as needed.
  • Design secure data ingestion and transformation frameworks leveraging Databricks services: Design delta or unmanaged tables, Create tasks for data, ingestion process, Create DAGs using Airflow to orchestrate creation of trusted and refined data.
  • Enforce data quality, lineage, and governance using Unity Catalog and/or Glue Catalog; embed expectations and validation into pipelines.
  • Drive Spark performance engineering: partitioning strategies, file sizing, AQE, broadcast joins, shuffle tuning, caching, spill/memory control, and job right-sizing to optimize cost.
  • Build reusable libraries, frameworks, and APIs in Python and/or Java; oversee unit, integration, and data validation testing.
  • Implement CI/CD for data projects (Git-based workflows), Terraform Infrastructure deployments environment promotion, and automated deployments; champion engineering standards and code reviews.

Required qualifications, capabilities, and skills:
  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • 8+ years of professional software/data engineering experience, including substantial production work with Spark on Databricks or EMR.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Strong proficiency in Python and/or Java for data processing, platform tooling, and automation.
  • Hands-on Databricks expertise (Delta Lake, Unity Catalog, Workflows, Repos/notebooks, SQL Warehouses).
  • Proven track record architecting and operating ETL/ELT pipelines (batch and streaming), with schema design/evolution, SLAs, and reliability engineering.
  • Deep skills in Spark performance tuning and Databricks cluster setup/optimization.
  • Strong SQL and analytics data modeling (dimensional/star schema; lakehouse best practices).
  • CI/CD and automation tooling for data (Git workflows, artifact management) and testing frameworks (pytest, JUnit).
  • Security-first mindset: roles/instance profiles, secret management, encryption-at-rest/in-transit, and network controls.

Preferred qualifications, capabilities, and skills:
  • Experience with Delta Live Tables and advanced governance (catalogs, grants, auditing) in Databricks.
  • AWS networking knowledge (VPC, subnets, routing, security groups) and data egress controls.
  • Experience with Terraform for Infra deployments
  • Cost optimization experience: autoscaling strategies, spot vs on-demand, auto-termination, storage layouts and compaction.
  • Observability for data systems (freshness/completeness metrics, lineage, SLAs, alerting).
  • Drive databricks performance tuning through liquid clustering or partitioning keys, familiarity with Airflow, Genie, Streamlit and React
  • Demonstrated leadership in code quality, reviews, testing strategy, CI/CD, and technical mentorship; excellent communication with stakeholders.

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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