Databricks Architect

Point C

. Design and implement scalable data platforms using Databricks, Apache Spark, Delta Lake, and SQL, producing solution architecture and technical design documentation .

Posted 10/2/2026full-timeRemote • United StatesMid-LevelSenior💰 $100,000 - $120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data platforms using Databricks, Apache Spark, and SQL, with a strong focus on data governance, performance optimization, and cloud integration on Azure. Proficient in building ETL/ELT pipelines and applying Medallion Architecture for enterprise data workloads.

Highest-signal resume keywords

DatabricksApache SparkPySparkSQLData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DevelopmentMedallion ArchitectureDelta LakeData WarehousingDimensional Modeling

Tools & Technologies

AzureAzure Data FactoryGitCI/CDTerraform

Certifications & Qualifications

Databricks Certifications

Industry Keywords

Data GovernanceUnity CatalogIAM/RBACCloud StorageDistributed Data Processing

Tech Stack

Tools & technologies

ApacheAzureCloudETLKafkaPySparkSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Design and implement scalable data platforms using Databricks, Apache Spark, Delta Lake, and SQL, producing solution architecture and technical design documentation
Develop Medallion Architecture (Bronze, Silver, Gold) for enterprise data workloads from multiple claim systems
Build and optimize production-grade ETL/ELT pipelines using Databricks Workflows, PySpark, and SQL
Work with ADF+ADLS ingest and existing kill-and-fill dimension patterns
Design and maintain data models and Delta tables, implementing schema evolution, time travel, partitioning, and optimization
Design solutions on Azure, integrating cloud storage and databases
Implement Unity Catalog, access controls, data governance, lineage, and security
Translate claim-system data dictionaries into Unity Catalog tables for reporting and APIs
Define and execute performance and cost-optimization strategies across the platform
Work with data engineers, analysts, and business stakeholders to translate requirements into technical designs
Establish CI/CD practices for Databricks notebooks, jobs, and infrastructure
Troubleshoot production data pipelines and support platform reliability

Requirements

What you’ll need

5–7 years of data engineering/cloud experience
Strong hands-on experience with Databricks and Apache Spark
Advanced PySpark and SQL
Strong understanding of Delta Lake and Medallion Architecture
Experience with at least one cloud platform: Azure
Knowledge of Data Governance, Unity Catalog, IAM/RBAC, and security
Experience with Git, CI/CD, and infrastructure-as-code concepts
Strong understanding of data warehousing, dimensional modeling, and distributed data processing
Preferred: Azure Data Factory
Preferred: Terraform
Preferred: Kafka or other streaming technologies
Preferred: Power BI platforms
Preferred: Databricks certifications
Preferred: Experience designing enterprise data lakes/lakehouses

Benefits

Comp & perks

Comprehensive medical, dental, vision, and life insurance coverage
401(k) retirement plan with employer match
Health Savings Account (HSA) & Flexible Spending Accounts (FSAs)
Paid time off (PTO) and disability leave
Employee Assistance Program (EAP)