Position: Senior Databricks Certified Data Engineer. Location: Remote. Based in Jersey City, New Jersey, United States. Must Have: Databricks Certified Data Engineer Professional Certification. Strongly preferred: Databricks Partner Champion Certificate. Requirements: 10+ years of experience in data engineering, data platforms and analytics; proficient in Python or Scala; extensive hands-on experience with Databricks and Apache Spark, including Spark runtime internals; familiarity with advanced Databricks concepts such as Genie Spaces, Genie Code, and Agents; demonstrated ability to lead large-scale projects and client engagements; working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with deep expertise in at least one; experience delivering end-to-end, highly scalable data architectures and production-grade pipelines (batch and streaming) using cloud-native components; strong CI/CD and MLOps capabilities; data modeling, warehousing and BI-serving patterns; Delta Lake ACID tables, schema evolution, merges, optimization and lakehouse storage patterns; ingestion patterns from databases, files and streams into bronze/silver/gold pipelines; orchestration and workflow tooling ( Lakeflow, SDP/Jobs ) and declarative pipelines; excellent communication, documentation and whiteboarding skills; ability to work with clients and manage conflicts.

Position: Senior Databricks Certified Data Engineer. Location: Remote. Based in Jersey City, New Jersey, United States. Must Have: Databricks Certified Data Engineer Professional Certification. Strongly preferred: Databricks Partner Champion Certificate. Requirements: 10+ years of experience in data engineering, data platforms and analytics; proficient in Python or Scala; extensive hands-on experience with Databricks and Apache Spark, including Spark runtime internals; familiarity with advanced Databricks concepts such as Genie Spaces, Genie Code, and Agents; demonstrated ability to lead large-scale projects and client engagements; working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with deep expertise in at least one; experience delivering end-to-end, highly scalable data architectures and production-grade pipelines (batch and streaming) using cloud-native components; strong CI/CD and MLOps capabilities; data modeling, warehousing and BI-serving patterns; Delta Lake ACID tables, schema evolution, merges, optimization and lakehouse storage patterns; ingestion patterns from databases, files and streams into bronze/silver/gold pipelines; orchestration and workflow tooling ( Lakeflow, SDP/Jobs ) and declarative pipelines; excellent communication, documentation and whiteboarding skills; ability to work with clients and manage conflicts.