Temporary Databricks Data Engineer Jobs (NOW HIRING)

Databricks Data Engineer

Our client is seeking a skilled and experienced Databricks Data Engineer to join our team. As a Databricks Data Engineer, you will be responsible for designing, developing, and implementing data engineering solutions using the Databricks platform to support data ingestion, transformation, performance reporting, analytics, sales incentive compensation processing, and enterprise data pipeline processes.

Responsibilities:

• Collaborate with business stakeholders to understand their data requirements and translate them into scalable technical solutions.
• Design and develop Databricks-based data pipelines, including data models, Delta Lake tables, and dashboards/notebooks.
• Responsible for the overall Databricks architecture to ensure new pipelines and enhancements to existing workflows are designed in an integrated and optimal manner.
• Maintain and optimize all current Databricks workspaces and pipelines; capture and deliver requirements for new or improved functionality to achieve further automation and integration of data and processes.
• Design and implement data pipelines to support Sales Incentive Compensation (SIC) processes, including quota management, attainment calculations, commission processing, and payout reporting.
• Partner with Sales Operations and Finance teams to understand incentive plan rules and translate them into accurate, auditable data transformations and models.
• Perform testing and debugging of data pipelines and notebooks to identify and resolve issues and ensure optimal performance.
• Provide technical support and troubleshooting for Databricks-based solutions, working closely with end-users and analysts to address their needs and resolve any data-related problems.
• Stay up to date with Databricks features and enhancements (Unity Catalog, Delta Live Tables, Photon, etc.) and proactively identify opportunities to leverage them to improve data quality, performance, and analytics capabilities.
• Collaborate with cross-functional teams, including finance, IT, and business intelligence teams, to ensure seamless integration and alignment of Databricks with other systems and processes.
• Document technical specifications, data models, pipeline configurations, and development processes to ensure knowledge transfer and maintain system documentation.

Requirements:

• At least 7 years of experience in data engineering, with a minimum of 3 years hands-on experience building and managing Databricks solutions.
• Extensive experience with Databricks platform components: Delta Lake, Delta Live Tables, Unity Catalog and Databricks Workflows.
• Strong proficiency in Python and/or Scala for data engineering; SQL expertise required.
• Strong experience with core data engineering practices including data ingestion, transformation (ETL/ELT), data modeling, and pipeline orchestration.
• Functional and technical experience with Sales Incentive Compensation (SIC) — including incentive plan design, quota allocation, attainment tracking, commission calculations, and payout processing.
• Familiarity with SIC platforms (e.g., Anaplan, Oracle ICM, Varicent) and experience integrating them with data engineering platforms is a strong plus.
• Ability to understand complex incentive compensation rules and model them accurately in data pipelines and transformation logic.
• Experience integrating Databricks with cloud platforms (Azure, AWS, or GCP) and data sources such as Azure Data Factory, Event Hubs, Kafka, or equivalent.
• Passion and ability to create holistic, end-to-end, integrated data solutions.
• Stakeholder management skills; ability to challenge constructively and translate complex business requirements into scalable data architectures — not just gather requirements.
• Strong analytical and problem-solving skills, with the ability to understand complex data requirements and implement reliable, efficient solutions.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders.
• Must work well in a team environment while being a resourceful, independent self-starter able to work effectively with minimal direction.
• Skilled at documenting complex data architectures and pipelines in a professional manner.
• Ability to work independently and manage multiple tasks and priorities in a fast-paced environment.
• Passion for data quality, performance optimization, and delivering excellent end-user data experiences.
• Databricks Certified Data Engineer Associate or Professional certification is a plus.