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Databricks Lakehouse Jobs (NOW HIRING)

Onebridge

Databricks Resident Solution Architect

$64.50 - $85/hr

Architect and guide implementation of Databricks-based data platforms, leveraging Lakehouse and Medallion architecture best practices. * Provide hands-on technical leadership across data engineering ...

Vytwo

AI/ML Architect with Databricks , AWS

Prosper, TX · On-site +1

$60 - $70/hr

AI/ML Architect with Databricks , AWS Location : Los Angeles CA (Hybrid) Hire type : FTE / CTH Role ... Must Demonstrate (Critical Competencies) Designing Databricksbased lakehouse architectures on AWS ...

Onebridge

Databricks Architect

$66.25 - $87/hr

Design and architect end-to-end data platforms using the Databricks Lakehouse architecture. * Define and implement scalable batch and streaming data pipelines using Apache Spark and Delta Lake.

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Databricks Lakehouse information

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How much do databricks lakehouse jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for databricks lakehouse in the United States is $67.68, according to ZipRecruiter salary data. Most workers in this role earn between $23.32 and $92.31 per hour, depending on experience, location, and employer.

Does Databricks have unlimited PTO?

As a Databricks Lakehouse employee, the company's PTO policies vary by location and role, and unlimited PTO is not universally offered. Many companies in the tech industry provide flexible or unlimited PTO options, but it is best to review specific company policies or employment agreements for accurate details.

What are some common challenges Databricks Lakehouse professionals face when integrating data from multiple sources, and how can they be addressed?

A frequent challenge for Databricks Lakehouse professionals is handling data integration from diverse sources with varying formats, quality, and update frequencies. Addressing this requires designing robust ETL pipelines, leveraging Delta Lake for data reliability, and employing tools like Auto Loader for scalable ingestion. Collaboration with data engineering and analytics teams is also key to ensure consistent data models and governance. Staying updated with platform features and best practices can significantly streamline these integration efforts.

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

To thrive as a Databricks Lakehouse Engineer, you need a solid background in data engineering, cloud computing (especially Azure or AWS), and proficiency with Spark, Python, or Scala. Experience with Databricks platform tools, Delta Lake, SQL, and certifications like Databricks Certified Data Engineer are highly valuable. Strong problem-solving skills, collaboration, and effective communication set exceptional professionals apart in this role. These abilities are crucial for building scalable data solutions, ensuring data quality, and driving business insights in complex data environments.

What are lakeflow jobs in Databricks?

Lakeflow jobs in Databricks refer to automated data processing tasks that run on the Lakehouse platform, enabling data engineers and analysts to orchestrate data pipelines efficiently. These jobs typically involve scheduling, monitoring, and managing workflows using Databricks tools like Jobs API or Databricks Workflows, often requiring knowledge of Spark, SQL, and cloud environments.

Is Databricks a lakehouse or warehouse?

Databricks is a unified data platform that primarily implements a lakehouse architecture, combining the scalability of data lakes with the management features of data warehouses. It enables data engineers and analysts to perform large-scale data processing, analytics, and machine learning within a single environment. While it supports data warehousing functionalities, its core design is centered around the lakehouse model.

Are Databricks high in demand?

Databricks Lakehouse professionals are in high demand due to the growing need for data engineering, analytics, and machine learning skills in organizations adopting cloud-based data platforms. Expertise in Spark, SQL, and cloud environments like AWS or Azure enhances job prospects in this field.

What is a Databricks Lakehouse?

A Databricks Lakehouse is a unified data platform that combines the best features of data lakes and data warehouses. It allows organizations to store all their data—structured, semi-structured, and unstructured—in one place, while providing tools for data engineering, analytics, machine learning, and business intelligence. The Lakehouse architecture simplifies data management, reduces costs, and improves collaboration across teams by eliminating data silos. Databricks Lakehouse is built on open standards and supports a wide range of data processing workloads, making it an ideal solution for modern data-driven enterprises.
Infographic showing various Databricks Lakehouse job openings in the United States as of June 2026, with employment types broken down into 91% Full Time, 3% Part Time, and 6% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $140,766 per year, or $67.7 per hour.
Senior Databricks Data Engineer (AWS) - Remote Opportunity

Senior Databricks Data Engineer (AWS) - Remote Opportunity

Booker DiMaio, LLC

Lanham, MD • Remote

$108K - $147K/yr

Full-time

Posted 3 days ago

Job description

Previous experience with a government client is required.
This is a remote position with a federal client who is based in Lanham, MD. Candidates must reside and perform work within the United States.
Position Overview
We are seeking two Senior Databricks Data Engineers to support a large-scale federal Enterprise Data Platform (EDP) modernization initiative. This role will focus on designing, developing, optimizing, and governing cloud-native data solutions utilizing Databricks Lakehouse technologies and Amazon Web Services (AWS).
The ideal candidate possesses extensive experience building enterprise-scale data pipelines, implementing data governance controls, optimizing large-scale data processing workloads, and enabling secure analytics capabilities in cloud environments. This position offers the opportunity to support a mission-critical federal data platform supporting trusted data intake, governed access, and advanced analytics capabilities.
Key Responsibilities
  • Design, develop, and maintain scalable data ingestion, transformation, and publishing pipelines utilizing Databricks and AWS services.
  • Implement and optimize Databricks Lakehouse capabilities including Unity Catalog, Delta Live Tables, Auto Loader, Databricks SQL, and Delta Sharing.
  • Build and maintain governed data products supporting operational, analytical, reporting, and machine learning workloads.
  • Develop and support medallion architecture data pipelines and enterprise data quality frameworks.
  • Implement data governance controls, metadata management, lineage tracking, and data retention policies.
  • Collaborate with cloud engineers, architects, cybersecurity specialists, and business stakeholders to deliver secure, production-ready solutions.
  • Optimize platform performance through partitioning, clustering, caching, workload tuning, and query optimization techniques.
  • Support analytics enablement through semantic layers, dashboards, reporting solutions, and self-service data access capabilities.
  • Participate in architecture reviews, operational readiness activities, platform modernization initiatives, and continuous improvement efforts.
  • Create and maintain technical documentation, design artifacts, operational procedures, and engineering standards.
Required Qualifications
  • Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline.
  • Minimum eight (8) years of experience in cloud-based data engineering, platform development, or data architecture.
  • Minimum three (3) years of hands-on Databricks experience in production environments.
  • Experience designing, developing, and supporting large-scale ETL/ELT solutions.
  • Strong experience with AWS services including S3, IAM, Glue, Athena, Lambda, Redshift, and CloudWatch.
  • Experience implementing enterprise data governance and security controls.
  • Strong SQL and Python development skills.
  • Experience working with data lakes, data warehouses, and cloud-native analytics platforms.
  • Strong troubleshooting, performance tuning, and optimization experience.
Preferred Qualifications
  • Databricks Certified Data Engineer Associate or Professional certification.
  • AWS Data Analytics Specialty certification.
  • Experience supporting federal government or highly regulated environments.
  • Experience with real-time streaming, CDC solutions, and event-driven architectures.
  • Familiarity with FedRAMP, FISMA, and NIST security frameworks.
  • Experience supporting large-scale enterprise data platforms.

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