Data Engineer

🚨 W2 Opportunity | Databricks Data Engineer | New York, NY (Hybrid) 📍 Location: New York, NY (Hybrid – Onsite 3 Days/Week) 💼 Employment: W2 Contract Only (No C2C / No Vendors) 🏢 Industry: Leading Insurance Client 📅 Duration: 6-Month Contract (Potential Extension) We're hiring an experienced Databricks Data Engineer to join a leading insurance client in New York. This role is ideal for data engineers with deep expertise in Databricks, Python, SQL, Delta Lake, and enterprise data engineering who enjoy building scalable data platforms and supporting analytics, reporting, and Sales Incentive Compensation (SIC) solutions . Required Skil ls✅ 7+ years of Data Engineering experien ce✅ 3+ years of hands-on Databricks experien ce✅ Delta Lake, Delta Live Tables, Unity Catalog, Databricks Workflo ws✅ Python and/or Sca la✅ Advanced S QL✅ ETL/ELT, Data Modeling & Pipeline Developme nt✅ Azure, AWS, or GCP integration experien ce✅ Azure Data Factory, Kafka, Event Hubs, or similar data integration too ls✅ Stakeholder management and solution architecture experien ce Preferred Qualificati • onsExperience supporting Sales Incentive Compensation (SIC) proces • sesKnowledge of incentive compensation platforms such as Anaplan, Oracle ICM, or Varic • entDatabricks Certified Data Engineer (Associate or Profession • al)Experience building enterprise-scale cloud data platfo • rmsStrong documentation and technical design ski llsKey Responsibilit • iesDesign, develop, and optimize scalable Databricks data pipelines and enterprise data solutio • ns.Build and maintain Delta Lake, Delta Live Tables, Unity Catalog, and Databricks Workflo • ws.Develop ETL/ELT pipelines for analytics, reporting, and operational data processi • ng.Design data models supporting Sales Incentive Compensation, quota management, commission calculations, and payout reporti • ng.Partner with business stakeholders, Finance, Sales Operations, and IT teams to translate business requirements into scalable technical solutio • ns.Optimize pipeline performance, troubleshoot data issues, and ensure high-quality, reliable data delive • ry.Integrate Databricks with cloud services and enterprise data sourc • es.Document data architectures, pipelines, and technical specificatio ns.