Data Architect

Papigen; Washington (District of Columbia); On-site; USD 130,000 - 190,000; Full time

Job summary

Papigen in Washington, DC is seeking an experienced Databricks Architect to lead enterprise-scale data and reporting initiatives. You will design lakehouse architectures, craft scalable data models, and build curated reporting datasets to enable high-quality analytics.

Collaborate with product owners, analysts, and data engineers in an Agile environment, guide notebooks and workflows, optimize performance, ensure data governance and security, and deliver architecture documentation and knowledge

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline.
• 8+ years of experience in data architecture, data engineering, analytics platforms, or related domains.
• Strong hands‑on experience with Databricks and modern lakehouse architectures.
• Proven expertise designing scalable enterprise data solutions and reporting data models.
• Experience with: Databricks Notebooks, Jobs & Workflows, Delta Lake, SQL, Data Transformation Frameworks.
• Strong SQL expertise and experience handling large-scale data processing workloads.
• Experience building ingestion and transformation pipelines from multiple enterprise data sources.
• Strong understanding of: Data Quality, Reconciliation, Metadata Management, Data Lineage, Data Governance.
• Experience implementing role-based access controls, security frameworks, and enterprise data policies.
• Proven track record optimizing Databricks performance, storage design, and workloads.
• Experience building curated data products, semantic layers, and enterprise reporting datasets.
• Ability to translate business requirements into scalable technical architectures and implementation designs.
• Strong documentation, communication, and stakeholder management skills.
• Experience working in Agile/Scrum teams and collaborating across business and technical functions.

Responsibilities

• Assess data sources, transformations, reporting requirements, and data flows across the enterprise.
• Define and implement scalable Databricks lakehouse architectures supporting reporting and analytics workloads.
• Design enterprise data models, curated datasets, semantic layers, and source-to-target mappings.
• Provide architectural guidance for Databricks notebooks, workflows, jobs, Delta tables, and orchestration processes.
• Design and optimize data ingestion, transformation pipelines.
• Establish data quality, reconciliation, metadata, lineage, governance, and auditability frameworks.
• Implement security controls, role-based access models, and data protection policies.
• Optimize Databricks workloads, SQL queries, storage structures, and resource utilization for performance and scalability.
• Support integration of Databricks data products with reporting and visualization platforms.
• Troubleshoot and resolve technical and data-related issues during development, testing, and deployment.
• Support SIT, UAT, production readiness, and post-deployment activities.
• Create architecture documents, technical specifications, and knowledge transfer materials.
• Collaborate with product owners, business analysts, data engineers, and reporting teams within Agile delivery environments.

Skills

Databricks

SQL

Data architecture

Data engineering

Data models

Data governance

Delta Lake

Agile/Scrum

Stakeholder management

Cloud data platforms

Education

Bachelor's degree

Tools

Databricks Notebooks

Jobs & Workflows

Delta Lake

SQL

Data Transformation Frameworks

Azure Data Factory

Azure Synapse

Azure Data Lake Storage

Job description

Role Summary:

We are seeking an experienced Databricks Architect to lead the design and implementation of enterprise-scale data and reporting solutions. The role will focus on architecting modern lakehouse environments, designing scalable data models, building curated reporting datasets, and enabling high-quality analytics through Databricks-based platforms. The ideal candidate will combine deep technical expertise with strong stakeholder collaboration skills to support enterprise reporting and analytical initiatives.

Scope of Work & Key Responsibilities:

• Assess existing data sources, transformations, reporting requirements, and data flows across the enterprise.
• Define and implement scalable Databricks lakehouse architectures supporting reporting and analytics workloads.
• Design enterprise data models, curated datasets, semantic layers, and source-to-target mappings.
• Provide architectural guidance for Databricks notebooks, workflows, jobs, Delta tables, and orchestration processes.
• Design and optimize data ingestion, transformation, and processing pipelines.
• Establish data quality, reconciliation, metadata, lineage, governance, and auditability frameworks.
• Implement security controls, role-based access models, and data protection policies.
• Optimize Databricks workloads, SQL queries, storage structures, and resource utilization for performance and scalability.
• Support integration of Databricks data products with reporting and visualization platforms.
• Troubleshoot and resolve technical and data-related issues during development, testing, and deployment.
• Support SIT, UAT, production readiness, and post-deployment activities.
• Create architecture documents, technical specifications, and knowledge transfer materials.
• Collaborate with product owners, business analysts, data engineers, and reporting teams within Agile delivery environments.

Required Skills & Experience:

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline.
• 8+ years of experience in data architecture, data engineering, analytics platforms, or related domains.
• Strong hands‑on experience with Databricks and modern lakehouse architectures.
• Proven expertise designing scalable enterprise data solutions and reporting data models.
• Experience with:
  • Databricks Notebooks
  • Jobs & Workflows
  • Delta Lake
  • SQL
  • Data Transformation Frameworks
• Strong SQL expertise and experience handling large-scale data processing workloads.
• Experience building ingestion and transformation pipelines from multiple enterprise data sources.
• Strong understanding of:
  • Data Quality
  • Reconciliation
  • Metadata Management
  • Data Lineage
  • Data Governance
• Experience implementing role-based access controls, security frameworks, and enterprise data policies.
• Proven track record optimizing Databricks performance, storage design, and workloads.
• Experience building curated data products, semantic layers, and enterprise reporting datasets.
• Ability to translate business requirements into scalable technical architectures and implementation designs.
• Strong documentation, communication, and stakeholder management skills.
• Experience working in Agile/Scrum teams and collaborating across business and technical functions.

Preferred Skills:

• Experience with Power BI or other enterprise reporting and visualization platforms.
• Exposure to Azure Data Factory, Azure Synapse, Azure Data Lake Storage, or similar cloud data services.
• Experience with Unity Catalog, data governance platforms, or enterprise metadata solutions.
• Knowledge of DataOps, CI/CD, and automated deployment practices for data platforms.
• Experience supporting enterprise reporting, executive dashboards, and analytics modernization initiatives.