

ScaleneWorks INC
Databricks Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Databricks Engineer in Wilmington, DE, on a contract basis. Key skills include Databricks, PySpark, and ETL modernization. Experience with Ab Initio migration and data governance is essential. The position requires five days onsite work.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 17, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Wilmington, DE
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🧠 - Skills detailed
#Data Processing #Datasets #Data Lineage #"ETL (Extract #Transform #Load)" #Snowflake #Data Engineering #Strategy #Cloud #Scala #Spark (Apache Spark) #Ab Initio #Data Pipeline #Databricks #PySpark #Data Architecture #Documentation #Batch #Deployment #Monitoring #Data Integrity #Data Governance #UAT (User Acceptance Testing) #Migration #Data Integration
Role description
Job Title :: Databricks Engineer
Location :: Wilmington, DE – 5 Days onsite role
Job Type: contract
Overview
We are seeking a Data Engineer to lead the modernization of legacy ETL systems by migrating Ab Initio workflows to scalable, modular PySpark pipelines on Databricks.
The role involves transforming complex data ecosystems into cloud-native architectures while ensuring data integrity, performance, and reliability.
Key Responsibilities
ETL Modernization & Development
• Analyze and migrate legacy ETL workflows from Ab Initio to PySpark-based pipelines
• Design and develop scalable data pipelines on Databricks
• Refactor monolithic processes into modular, reusable components
• Leverage existing enterprise datasets to avoid redundancy
Data Integration & Processing
• Build and maintain ETL/ELT pipelines integrating data from Snowflake and other sources
• Process and publish enriched datasets for downstream applications
• Support batch and near real-time data processing
Data Lineage & Optimization
• Create end-to-end data lineage and data flow diagrams
• Identify redundancies and drive process consolidation and optimization
• Ensure adherence to data governance and quality standards
Testing & Validation
• Develop unit, integration, and reconciliation frameworks
• Perform dual-run comparisons with legacy systems
• Validate outputs in UAT and pre-production environments
Deployment & Operations
• Support cutover and migration strategy from legacy systems
• Decommission legacy workflows and optimize scheduling (e.g., Control-M)
• Develop runbooks, monitoring, and operational documentation
Collaboration
• Work with data architects, analysts, and downstream application teams
• Coordinate user acceptance testing (UAT/FAT) and stakeholder sign-offs
Job Title :: Databricks Engineer
Location :: Wilmington, DE – 5 Days onsite role
Job Type: contract
Overview
We are seeking a Data Engineer to lead the modernization of legacy ETL systems by migrating Ab Initio workflows to scalable, modular PySpark pipelines on Databricks.
The role involves transforming complex data ecosystems into cloud-native architectures while ensuring data integrity, performance, and reliability.
Key Responsibilities
ETL Modernization & Development
• Analyze and migrate legacy ETL workflows from Ab Initio to PySpark-based pipelines
• Design and develop scalable data pipelines on Databricks
• Refactor monolithic processes into modular, reusable components
• Leverage existing enterprise datasets to avoid redundancy
Data Integration & Processing
• Build and maintain ETL/ELT pipelines integrating data from Snowflake and other sources
• Process and publish enriched datasets for downstream applications
• Support batch and near real-time data processing
Data Lineage & Optimization
• Create end-to-end data lineage and data flow diagrams
• Identify redundancies and drive process consolidation and optimization
• Ensure adherence to data governance and quality standards
Testing & Validation
• Develop unit, integration, and reconciliation frameworks
• Perform dual-run comparisons with legacy systems
• Validate outputs in UAT and pre-production environments
Deployment & Operations
• Support cutover and migration strategy from legacy systems
• Decommission legacy workflows and optimize scheduling (e.g., Control-M)
• Develop runbooks, monitoring, and operational documentation
Collaboration
• Work with data architects, analysts, and downstream application teams
• Coordinate user acceptance testing (UAT/FAT) and stakeholder sign-offs






