Data Quality

Databricks Data Engineer – Sales Incentive Compensation | New York, NY

Databricks Data Engineer – Sales Incentive Compensation

πŸ“ Location: New York, New York
🏒 Work Arrangement: Hybrid
πŸ“„ Contract Length: Six Months
πŸ’° Hourly Rate: Approximately $75 per hour
πŸ’Ό Employment Type: Contract
🚫 Visa Sponsorship: Not Available
🚚 Relocation Assistance: Not Available
🏦 Industry: Insurance and Financial Services

Build the Data Infrastructure Behind Enterprise Sales Compensation

A leading global organization is seeking an experienced Databricks Data Engineer to design, develop and optimize enterprise data solutions supporting analytics, performance reporting and Sales Incentive Compensation.

This is not purely a pipeline-development position. The successful candidate will combine strong Databricks engineering expertise with an understanding of incentive compensation processes, including quota allocation, attainment calculations, commission processing and payout reporting.

You will work closely with Sales Operations, Finance, Business Intelligence and technology teams to translate complex business rules into scalable, accurate and auditable data solutions.

Why This Opportunity Stands Out

This opportunity will allow you to:

  • Own the design and development of enterprise Databricks solutions

  • Influence the wider Databricks architecture and technical roadmap

  • Build data pipelines supporting business-critical compensation processes

  • Work with Delta Lake, Delta Live Tables, Unity Catalog and Databricks Workflows

  • Translate complex incentive-plan rules into reliable transformation logic

  • Improve automation, integration, data quality and platform performance

  • Partner directly with senior Finance, Sales Operations and technology stakeholders

  • Deliver solutions that directly influence commission and compensation accuracy

What You’ll Be Doing

Databricks Architecture and Engineering

  • Design, develop and implement scalable Databricks-based data solutions

  • Build and maintain data pipelines supporting ingestion, transformation, reporting and analytics

  • Develop data models, Delta Lake tables, notebooks and reporting datasets

  • Take ownership of the overall Databricks architecture

  • Ensure new pipelines and enhancements integrate effectively with existing workflows

  • Maintain and optimize Databricks workspaces, pipelines and orchestration processes

  • Identify opportunities to improve automation, performance and data integration

  • Design reliable ETL and ELT processes across multiple enterprise data sources

Sales Incentive Compensation

  • Build data pipelines supporting Sales Incentive Compensation processes

  • Translate incentive-plan rules into accurate and auditable data transformations

  • Support quota allocation and quota-management processes

  • Develop logic for attainment tracking and performance calculations

  • Support commission calculations and payout processing

  • Produce reliable datasets for compensation reporting and reconciliation

  • Work closely with Sales Operations and Finance to understand plan structures and business rules

  • Ensure calculation logic is transparent, documented and capable of being audited

  • Integrate incentive-compensation platforms with enterprise data and analytics solutions

Performance and Data Quality

  • Test, debug and optimize Databricks pipelines and notebooks

  • Investigate and resolve data-quality, performance and integration issues

  • Improve the reliability and efficiency of existing workflows

  • Implement appropriate controls and validation processes

  • Monitor data pipelines and troubleshoot failures or inconsistencies

  • Deliver a high-quality experience for analysts and other data consumers

Stakeholder and Technical Collaboration

  • Work with business stakeholders to understand complex data requirements

  • Translate functional requirements into scalable technical architectures

  • Challenge requirements constructively when a more effective solution is available

  • Partner with Finance, Sales Operations, IT and Business Intelligence teams

  • Provide technical support to analysts and end users

  • Communicate technical concepts clearly to both technical and non-technical audiences

  • Manage multiple priorities within a fast-paced enterprise environment

Documentation and Platform Development

  • Document data architectures, models, pipelines and configuration decisions

  • Produce clear technical specifications and development documentation

  • Maintain documentation to support knowledge transfer and long-term platform ownership

  • Stay current with Databricks capabilities and platform enhancements

  • Identify opportunities to use features such as Unity Catalog, Delta Live Tables and Photon

What You’ll Bring

Essential Databricks and Data Engineering Experience

  • At least seven years of professional data-engineering experience

  • A minimum of three years of hands-on Databricks experience

  • Extensive experience building and managing production Databricks solutions

  • Strong knowledge of:

    • Delta Lake

    • Delta Live Tables

    • Unity Catalog

    • Databricks Workflows

    • Databricks notebooks and workspaces

  • Advanced proficiency in Python and/or Scala

  • Strong SQL development expertise

  • Experience with data ingestion, transformation, ETL/ELT and data modelling

  • Experience designing and orchestrating enterprise data pipelines

  • Strong understanding of data quality, scalability and performance optimization

Sales Incentive Compensation Experience

  • Functional and technical experience with Sales Incentive Compensation processes

  • Understanding of incentive-plan design and compensation rules

  • Experience supporting quota allocation and management

  • Knowledge of sales-attainment calculations

  • Experience with commission calculation and payout processing

  • Ability to model complex incentive rules within data pipelines and transformation logic

  • Experience partnering with Sales Operations and Finance stakeholders

Cloud and Integration Experience

  • Experience integrating Databricks with at least one major cloud platform:

    • Microsoft Azure

    • Amazon Web Services

    • Google Cloud Platform

  • Experience working with integration and ingestion technologies such as:

    • Azure Data Factory

    • Azure Event Hubs

    • Apache Kafka

    • Comparable cloud-based data-integration tools

  • Ability to create holistic, end-to-end data solutions rather than isolated pipelines

Professional Capabilities

  • Strong stakeholder-management and consulting skills

  • Ability to translate complex business requirements into scalable data architectures

  • Excellent analytical and problem-solving capabilities

  • Strong written and verbal communication skills

  • Ability to work effectively with cross-functional teams

  • Resourceful and comfortable working with minimal direction

  • Strong technical-documentation skills

  • Ability to manage competing priorities and deadlines

  • Bachelor’s degree in Computer Science, Data Engineering, Information Technology or a related discipline

Preferred Experience

  • Experience integrating Databricks with platforms such as:

    • Anaplan

    • Oracle Incentive Compensation

    • Varicent

    • Comparable Sales Performance Management platforms

  • Databricks Certified Data Engineer Associate certification

  • Databricks Certified Data Engineer Professional certification

  • Experience using Photon to improve query and workload performance

  • Previous experience within insurance, financial services or another large regulated enterprise

  • Experience delivering auditable financial or compensation-related data solutions

The Ideal Candidate

The ideal candidate will be an experienced Databricks engineer who understands that compensation data requires exceptional accuracy, traceability and control.

You will be comfortable moving between detailed technical development and strategic conversations with Finance, Sales Operations and technology leaders. You should be willing to challenge requirements constructively, propose stronger architectural solutions and take ownership of delivery from initial design through testing, deployment and production support.

Most importantly, you will be able to combine enterprise data-engineering expertise with a practical understanding of how incentive plans, quotas, attainment calculations, commissions and payouts operate.

Contract Details

  • Initial Contract: Six months

  • Hourly Rate: Approximately $75 per hour

  • Location: New York, New York

  • Working Arrangement: Hybrid

  • Visa Sponsorship: Not available

  • Relocation Assistance: Not available

Ready to Build Business-Critical Data Solutions?

If you have deep Databricks expertise and experience translating complex Sales Incentive Compensation processes into scalable, accurate and auditable data solutions, this position offers the opportunity to make an immediate impact within a major enterprise environment.

 

Data Engineer | Azure, Databricks, Python, SQL, Spark | Hybrid – Netherlands (€3,500–€5,000/month)

Data Engineer

πŸ“ Location: Eindhoven area or Randstad, Netherlands (Hybrid – 3 office days / 2 home days)
πŸ’Ό Employment Type: Full-time
πŸ’΅ Salary: €3,500 – €5,000 per month (€45,360 – €64,800 annually)
🎯 Experience Level: Mid-level | 2–3 years’ experience

About the Role

Do you love working with data β€” from digging into sources and writing clean ingestion scripts to ensuring a seamless flow into a data lake? As a Data Engineer, you’ll design and optimize data pipelines that transform raw information into reliable, high-quality datasets for enterprise clients.

You’ll work with state-of-the-art technologies in the cloud (Azure, Databricks, Fabric) to build solutions that deliver business-critical value. In this role, data quality, stability, and monitoring are key β€” because the pipelines you create will be used in production environments.

Key Responsibilities

  • Develop data connectors and processing solutions using Python, SQL, and Spark.

  • Define validation tests within pipelines to guarantee data integrity.

  • Implement monitoring and alerting systems for early issue detection.

  • Take the lead in troubleshooting incidents to minimize user impact.

  • Collaborate with end users to validate and continuously improve solutions.

  • Work within an agile DevOps team to build, deploy, and optimize pipelines.

Requirements

  • πŸŽ“ Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

  • 2–3 years of relevant experience in data ingestion and processing.

  • Strong knowledge of SQL, Python, and Spark.

  • Familiarity with container environments (e.g., Kubernetes).

  • Experience with Azure Data Factory, Databricks, or Fabric is a strong plus.

  • Experience with data model management and dashboarding (e.g., PowerBI) preferred.

  • Team player with strong communication skills in Dutch and English.

  • Familiarity with enterprise data platforms and data lakes is ideal.

What We Offer

  • πŸ’Ά Salary: €3,500 – €5,000 per month

  • 🌴 26 vacation days

  • πŸš— Lease car or mobility budget (€600)

  • πŸ’» Laptop & mobile phone

  • πŸ’Έ €115 monthly cost allowance

  • 🏦 50% employer contribution for health insurance

  • πŸ“ˆ 60% employer contribution for pension scheme

  • 🎯 Performance-based bonus

  • πŸ“š Training via in-house Academy (hard & soft skills)

  • πŸ‹οΈ Free use of on-site gym

  • 🌍 Hybrid work model (3 days in office, 2 days at home)

  • 🀝 Start with a 12-month contract, with option to move to indefinite after evaluation

Ideal Candidate

You are a hands-on data engineer who enjoys data wrangling and building robust pipelines. You take pride in seeing your code run smoothly in production and know how to troubleshoot quickly when issues arise. With strong technical skills in SQL, Python, and Spark, plus familiarity with cloud platforms like Azure, you’re ready to contribute to impactful enterprise projects.

πŸ‘‰ Ready to make data flow seamlessly and create business value? Apply now to join a passionate, innovation-driven team.