Placement Role - Databricks Consultant with PySpark/Python and Delta Lake exp - Hybrid - NY

Databricks Solution Architect (Only G.C / U.S.C) 6+Months New York, NY (Onsite) **Company Overview:** We are a leading technology company specializing in data analytics and cloud solutions. Our innovative approach helps businesses harness the power of data to drive growth and efficiency. We are seeking a skilled Databricks Architect with extensive experience to join our dynamic team and contribute to building cutting-edge Lakehouse solutions. **Key Responsibilities:** - Design and implement sca

Role: Databricks Architect Location: NYC, NY (Hybrid role- 3days onsite in a week) Duration: Long Term Job description: We are seeking a Databricks Architect with deep MLOps expertise to lead the design and implementation of scalable machine learning platforms within a banking environment. This role will focus on building production-grade ML pipelines, governance frameworks, and model lifecycle management aligned with model risk management (MRM) standards. Key Responsibilities: Architect and imp

Position:Data Architect (Databricks Lakehouse) Location: NYC NY Duration: 6+ Months Job Details: Own the target-state architecture in Databricks and actively contribute to pipeline development. Define how API/FTP data flows into Bronze/Silver/Gold layers with cleansing and enrichment logic. Key Responsibilities Design Databricks Lakehouse architecture (Bronze/Silver/Gold)Define ingestion patterns for API & FTPArchitect scalable cleansing & enrichment frameworksTranslate legacy SQL logic into S

Hi, I would like to share an excellent opening Contact Databricks Architect with MLOps do go through the details and kindly send me the updated resume. Location : NYC, NY (Hybrid) Type of Hire : Contract Mode of interview : WebEx / Teams Required Qualifications Experience in data/ML engineering or architectureHands-on Databricks experienceStrong expertise in MLOps frameworks and production ML systemsDeep experience with:MLflowPython (PySpark, Pandas, scikit-learn)Spark-based data processingExp