Data Pipeline Engineer ____ Remote (Ohio, USA) ____ Contract in , United States

Data Pipeline EngineerLocation: Remote (Ohio, USA) Employment Type: Contract, Long TermPrior experience with Cardinal is highly .Job Overview: We are seeking a highly skilled Data Pipeline Engineer to design, build, and optimize data pipelines in a cloud-based environment. The ideal candidate will have strong expertise in Databricks (Python & PySpark), Azure SQL, and data modeling, with a solid understanding of ETL/ELT design patterns. You will be responsible for ensuring the performance, reliability, and scalability of our data solutions while collaborating with cross-functional teams.Key Responsibilities:Design, develop, and maintain scalable and efficient data pipelines using Databricks and Azure Data Services.Implement robust ETL/ELT frameworks for structured and unstructured data.Build and optimize data models to support analytics, reporting, and machine learning workloads.Collaborate with data architects, analysts, and DevOps teams to define data requirements and solutions.Ensure data quality, governance, and security across all data layers.Leverage Docker and Azure Kubernetes Service (AKS) for automation, containerization, and scalability.Monitor, troubleshoot, and optimize data pipeline performance and resource utilization.Document technical processes, data flows, and best practices.Must-Have Skills:Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.9+ years of overall IT experience is requiredStrong experience with Databricks (Python, SQL, PySpark).Proficiency with Azure SQL Server (Managed Instance, Azure SQL DB, SQL Server on VMs).Expertise in Data Modeling, ETL/ELT frameworks, and data architecture patterns.Hands-on experience with Docker and Azure Kubernetes Service (AKS).Experience in performance optimization, pipeline orchestration, and CI/CD integration.Nice-to-Have Skills:Experience with Azure Data Factory, Synapse Analytics, or Power BI integration.Familiarity with Delta Lake, Parquet, and Data Lakehouse architectures.Exposure to DevOps practices and infrastructure as code (IaC) in Azure.