ELT

Databricks Data Engineer โ€“ Sales Incentive Compensation | New York, NY

Databricks Data Engineer โ€“ Sales Incentive Compensation

๐Ÿ“ Location: New York, New York
๐Ÿข Work Arrangement: Hybrid
๐Ÿ“„ Contract Length: Six Months
๐Ÿ’ฐ Hourly Rate: Approximately $75 per hour
๐Ÿ’ผ Employment Type: Contract
๐Ÿšซ Visa Sponsorship: Not Available
๐Ÿšš Relocation Assistance: Not Available
๐Ÿฆ 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 Youโ€™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 Youโ€™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

  • Bachelorโ€™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 | AWS, Python & Snowflake | Ridgefield, CT (Hybrid) | $140Kโ€“$185K

๐Ÿง  Data Engineer

Before reading further, here are three non-negotiables that the client has made absolutely clear:

This is a Direct Hire (W2) permanent position. No C2C, no 1099, no third parties.

Candidates must NOT require sponsorship now or in the future. We can only consider US Citizens or Green Card holders who can work long-term without restriction.

The role is Hybrid โ€” non-negotiable. You must be onsite 2โ€“3 days per week in Ridgefield, CT, so candidates must already live within commuting distance or be willing to relocate.
(The good news: the company offers excellent benefits and is open to relocation support or a sign-on bonus for the right hire.)

๐Ÿ“ Location: Ridgefield, Connecticut (Hybrid โ€“ 2โ€“3 days onsite per week)
๐Ÿ’ผ Openings: 2
๐Ÿข Industry: Information Technology / Life Sciences
๐ŸŽ“ Education: Bachelorโ€™s degree in Computer Science, MIS, or related field (Masterโ€™s preferred)
๐Ÿšซ Visa Sponsorship: Not available
๐Ÿšš Relocation: Available for the ideal candidate
๐Ÿ’ฐ Compensation: $140,000 โ€“ $185,000 base salary + full benefits
๐Ÿ•“ Employment Type: Full-Time | Permanent

๐ŸŒŸ The Opportunity

Step into the future with a global leader in healthcare innovation โ€” where Data and AI drive transformation and impact millions of lives.

As part of the Enterprise Data, AI & Platforms (EDP) team, youโ€™ll join a high-performing group thatโ€™s building scalable, cloud-based data ecosystems and shaping the companyโ€™s data-driven future.

This role is ideal for a hands-on Data Engineer who thrives on designing, optimizing, and maintaining robust data pipelines in the cloud, while collaborating closely with architects, scientists, and business stakeholders across the enterprise.

๐Ÿงญ Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines and integration frameworks to enable advanced analytics and AI use cases.

  • Collaborate with data architects, modelers, and data scientists to evolve the companyโ€™s cloud-based data architecture strategy (data lakes, warehouses, streaming analytics).

  • Optimize and manage data storage solutions (e.g., S3, Snowflake, Redshift), ensuring data quality, integrity, and security.

  • Implement data validation, monitoring, and troubleshooting processes to ensure high system reliability.

  • Work cross-functionally with IT and business teams to understand data requirements and translate them into scalable solutions.

  • Document architecture, workflows, and best practices to support transparency and continuous improvement.

  • Stay current with emerging data engineering technologies, tools, and methodologies, contributing to innovation across the organization.

๐Ÿง  Core Requirements

Technical Skills

โœ… Hands-on experience with AWS data services such as Glue, Lambda, Athena, Step Functions, and Lake Formation.
โœ… Strong proficiency in Python and SQL for data manipulation and pipeline development.
โœ… Experience in data warehousing and modeling (dimensional modeling, Kimball methodology).
โœ… Familiarity with DevOps and CI/CD practices for data solutions.
โœ… Experience integrating data between applications, data warehouses, and data lakes.
โœ… Understanding of data governance, metadata management, and data quality principles.

Cloud & Platform Experience

  • Expertise in AWS, Azure, or Google Cloud Platform (GCP) โ€“ AWS preferred.

  • Knowledge of ETL/ELT tools such as Apache Airflow, dbt, Azure Data Factory, or AWS Glue.

  • Experience with Snowflake, PostgreSQL, MongoDB, or other modern database systems.

Education & Experience

๐ŸŽ“ Bachelorโ€™s degree in Computer Science, MIS, or related field
๐Ÿ’ผ 5โ€“7 years of professional experience in data engineering or data platform development
โญ AWS Solutions Architect certification is a plus

๐Ÿš€ Preferred Skills & Attributes

  • Deep knowledge of big data technologies (Spark, Hadoop, Flink) is a strong plus.

  • Proven experience troubleshooting and optimizing complex data pipelines.

  • Strong problem-solving skills and analytical mindset.

  • Excellent communication skills for collaboration across technical and non-technical teams.

  • Passion for continuous learning and data innovation.

๐Ÿ’ฐ Compensation & Benefits

๐Ÿ’ต Base Salary: $140,000 โ€“ $185,000 (commensurate with experience)
๐ŸŽฏ Bonus: Role-based variable incentive
๐Ÿ’Ž Benefits Include:

  • Comprehensive health, dental, and vision coverage

  • Paid vacation and holidays

  • 401(k) retirement plan

  • Wellness and family support programs

  • Flexible hybrid work environment

๐Ÿงฉ Candidate Snapshot

  • Experience: 5โ€“7 years in data engineering or related field

  • Key Skills: AWS Glue | Python | SQL | ETL | CI/CD | Snowflake | Data Modeling | Cloud Architecture

  • Seniority Level: Midโ€“Senior

  • Work Arrangement: 2โ€“3 days onsite in Ridgefield, CT

  • Travel: Occasional

๐Ÿš€ Ready to power the future of data-driven healthcare?
Join a global data and AI team committed to harnessing the power of cloud and analytics to drive discovery, innovation, and meaningful impact worldwide.