Databricks Architect

LouisianaNOW.Jobs

. Provide technical and architectural leadership for Databricks, modern data platforms, Lakehouse architectures, and cloud-native data solutions .

Posted 11/11/2026full-timeUnited StatesSeniorLead💰 $114,800 - $267,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable enterprise data architectures using Databricks and Lakehouse technologies, while optimizing data pipelines and ensuring data governance and security. Proven ability to lead technical teams and deliver complex data solutions in cloud environments.

Highest-signal resume keywords

Databricks Solutions DesignData Lakehouse ArchitectureApache Spark OptimizationEnterprise Data GovernanceCloud Integration (Azure, AWS, GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DatabricksDelta LakeApache SparkPythonScalaSQLETL/ELT Pipeline DevelopmentData ModelingData Quality FrameworksData Mesh

Soft Skills

Technical LeadershipMentoringCommunicationConsultingProblem-Solving

Tools & Technologies

Azure Data FactoryCI/CDDevOpsDataOpsAgile Methodologies

Certifications & Qualifications

Databricks Certified Data Engineer Professional

Industry Keywords

Cloud-Native Data SolutionsData GovernanceMetadata ManagementData LineageEnterprise Data Cataloging

Tech Stack

Tools & technologies

ApacheAWSAzureCloudETLGoogle Cloud PlatformPythonScalaSparkSQLUnity

About the role

Key responsibilities & impact

Provide technical and architectural leadership for Databricks, modern data platforms, Lakehouse architectures, and cloud-native data solutions
Design and implement scalable enterprise data architectures using Databricks, Delta Lake, Delta Lake UniForm/Iceberg interoperability, Lakeflow Declarative Pipelines, and Unity Catalog
Lead end-to-end Data Lakehouse architecture and development across ingestion, transformation, modeling, orchestration, storage, analytics, and consumption layers
Design and optimize data pipelines integrating structured, semi-structured, and unstructured data from multiple enterprise source systems
Establish standards and best practices for governance, security, access controls, metadata, data quality, reliability, and observability
Optimize Spark workloads, Databricks compute, storage, and platform configurations for performance, scalability, reliability, and cost efficiency
Perform coding, solution prototyping, design reviews, troubleshooting, and resolution of critical technical issues
Partner with clients and stakeholders to translate business challenges into scalable data and analytics solutions
Lead and mentor data engineers and technical team members
Support analytics, AI/ML, and Generative AI use cases through governed enterprise data foundations
Collaborate with cloud, security, infrastructure, application, and analytics teams
Support proposals, statements of work, technical presentations, solution development, and account growth strategies

Requirements

What you’ll need

10+ years of experience in data engineering, data architecture, or related disciplines
5+ years of hands-on experience designing and delivering end-to-end Databricks solutions in cloud environments
Deep expertise with Databricks, Lakehouse architecture, Apache Spark, Databricks SQL, Delta Lake, Unity Catalog, notebooks, compute, jobs, workflows, and workspace management
Strong hands-on development experience with Python and/or Scala, Spark, SQL, and distributed data processing
Experience designing and implementing enterprise-scale ETL/ELT and data integration pipelines using Databricks and Spark
Hands-on experience integrating Databricks with Microsoft Azure, AWS, or Google Cloud Platform (GCP)
Strong understanding of logical and physical data modeling for enterprise analytics, reporting, and data products
Experience implementing enterprise data governance and security, including Unity Catalog, role-based access control, lineage, metadata management, and compliance requirements
Experience optimizing Spark workloads, compute configurations, storage, and data pipelines for performance and cost efficiency
Experience designing highly available, reliable, scalable, and maintainable enterprise data platforms
Ability and willingness to remain hands-on with architecture, development, coding, troubleshooting, and technical problem-solving
Proven track record delivering multiple complex, enterprise-scale Databricks implementations through production support
Strong communication and consulting skills
Ability to provide technical leadership and mentor engineering teams
Bachelor’s degree in a related technical field is preferred; equivalent education and relevant professional experience will be considered in lieu of a degree
Databricks Certified Data Engineer Professional or other relevant Databricks certification is desired
Experience with Azure Data Factory or comparable cloud-native orchestration technologies is desired
Experience with DevOps/DataOps, CI/CD, automated testing, source control, infrastructure automation, and Agile delivery methodologies is desired
Experience with metadata management, enterprise data cataloging, data lineage, and data quality frameworks is desired
Experience with data mesh, domain-oriented architectures, Lakebridge, migration and modernization tooling, multi-workspace/multi-region governance, AI/ML, Generative AI, consulting, proposals, solution estimation, or SOW development is desired

Benefits

Comp & perks

Competitive compensation
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Well being programs
Ownership/share participation as CGI Partners
Reasonable accommodations for qualified individuals with disabilities