DHI Group, Inc.
Data Engineer - Databricks
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer specializing in Azure Databricks for a 6-month contract, offering hourly compensation. Remote or hybrid work is available. Key skills include Databricks, Azure Cloud, Python, and experience with financial systems or agricultural finance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 6, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
-
🧠 - Skills detailed
#API (Application Programming Interface) #Cloud #Documentation #GraphQL #BI (Business Intelligence) #Data Lake #DevOps #Databricks #PySpark #Spark (Apache Spark) #Data Warehouse #Data Integration #Scala #Data Accuracy #GitHub #"ETL (Extract #Transform #Load)" #Batch #GIT #Storage #Data Governance #Vault #Azure #Azure DevOps #Data Quality #Programming #CLI (Command-Line Interface) #TypeScript #REST (Representational State Transfer) #Data Processing #Azure Databricks #Docker #React #Compliance #Azure cloud #Spark SQL #Azure CLI (Azure Command Line Interface) #PostgreSQL #Delta Lake #Security #Classification #Redis #Data Engineering #Python #SQL (Structured Query Language)
Role description
Azure Databricks Data Engineer
Contract Duration: 6 months
Location: Remote or Hybrid (Kansas City area)
Compensation: Hourly (Contract Position)
Work Authorization: Must be legally authorized to work in the U.S. without sponsorship
About the Project
Join CFA’s initiative to extend our industry-renowned lending platform through Azure Databricks-powered data integration. You will architect and build a centralized data lake that unifies data across systems including Salesforce, loan servicing platforms, document management systems (e.g., DocuSign, Conga), and more — delivering a single source of truth for agricultural finance operations.
Core Responsibilities
• Design and implement Azure Databricks-based data lake architecture integrating multiple enterprise data sources
• Build real-time streaming and batch pipelines for Salesforce, loan servicing, and document management systems
• Develop robust data quality, validation, and cleansing processes
• Create analytics-ready data structures optimized for BI and operational reporting
• Implement data governance and security aligned with SOC 2 Type II compliance
• Collaborate with API/service teams to expose unified data via REST and GraphQL endpoints
Required Technical Skills
• Databricks Expertise: Delta Lake, Spark SQL, PySpark
• Azure Cloud Stack: Data Factory, Event Hubs, Blob Storage, Key Vault, Azure AD
• ETL/Data Engineering: Pipeline design, dimensional/star schema modeling, data warehouse patterns
• Programming: Python (primary), SQL; Scala is a plus
• Integration Experience: Salesforce APIs, REST/SOAP, document system connectors
• Data Processing: Real-time ingestion & scheduled sync strategies
• Security: AES-256 encryption, TLS 1.3, RBAC, data classification
Preferred Qualifications
• Experience with loan servicing or financial systems
• Familiarity with DocuSign, Conga, and email archival systems
• GraphQL experience for data exposure
• Azure or Databricks certifications (e.g., Data Engineer Associate)
• Background in agricultural finance or fintech
• Experience with SOC 2 or similar compliance frameworks
Technical Environment
• Cloud: Azure (Databricks, Data Factory, Blob Storage, Key Vault)
• Tools: Git/GitHub, Azure DevOps, GitHub Actions, Docker, Azure CLI
• Data Sources: Salesforce, NLS, DocuSign, Conga, email archives
• Backend: Node.js, Python APIs, PostgreSQL, Redis
• Frontend: React 18+, TypeScript (basic understanding helpful)
Success Criteria
• Fully integrated, synchronized data lake across all source systems
• 95% data accuracy and completeness
• <5-minute latency on real-time data streams
• Thorough documentation to ensure maintainability
• SOC 2 Type II-compliant security implementation
Azure Databricks Data Engineer
Contract Duration: 6 months
Location: Remote or Hybrid (Kansas City area)
Compensation: Hourly (Contract Position)
Work Authorization: Must be legally authorized to work in the U.S. without sponsorship
About the Project
Join CFA’s initiative to extend our industry-renowned lending platform through Azure Databricks-powered data integration. You will architect and build a centralized data lake that unifies data across systems including Salesforce, loan servicing platforms, document management systems (e.g., DocuSign, Conga), and more — delivering a single source of truth for agricultural finance operations.
Core Responsibilities
• Design and implement Azure Databricks-based data lake architecture integrating multiple enterprise data sources
• Build real-time streaming and batch pipelines for Salesforce, loan servicing, and document management systems
• Develop robust data quality, validation, and cleansing processes
• Create analytics-ready data structures optimized for BI and operational reporting
• Implement data governance and security aligned with SOC 2 Type II compliance
• Collaborate with API/service teams to expose unified data via REST and GraphQL endpoints
Required Technical Skills
• Databricks Expertise: Delta Lake, Spark SQL, PySpark
• Azure Cloud Stack: Data Factory, Event Hubs, Blob Storage, Key Vault, Azure AD
• ETL/Data Engineering: Pipeline design, dimensional/star schema modeling, data warehouse patterns
• Programming: Python (primary), SQL; Scala is a plus
• Integration Experience: Salesforce APIs, REST/SOAP, document system connectors
• Data Processing: Real-time ingestion & scheduled sync strategies
• Security: AES-256 encryption, TLS 1.3, RBAC, data classification
Preferred Qualifications
• Experience with loan servicing or financial systems
• Familiarity with DocuSign, Conga, and email archival systems
• GraphQL experience for data exposure
• Azure or Databricks certifications (e.g., Data Engineer Associate)
• Background in agricultural finance or fintech
• Experience with SOC 2 or similar compliance frameworks
Technical Environment
• Cloud: Azure (Databricks, Data Factory, Blob Storage, Key Vault)
• Tools: Git/GitHub, Azure DevOps, GitHub Actions, Docker, Azure CLI
• Data Sources: Salesforce, NLS, DocuSign, Conga, email archives
• Backend: Node.js, Python APIs, PostgreSQL, Redis
• Frontend: React 18+, TypeScript (basic understanding helpful)
Success Criteria
• Fully integrated, synchronized data lake across all source systems
• 95% data accuracy and completeness
• <5-minute latency on real-time data streams
• Thorough documentation to ensure maintainability
• SOC 2 Type II-compliant security implementation
