Data Architect

Databricks ArchitectJob SummaryWe are seeking a highly skilled Databricks Architect to design, implement, and optimize data solutions on the Databricks platform. The ideal candidate will have deep expertise in cloud-based data engineering, big data processing, and analytics, and a strong understanding of data architecture principles. You will play a pivotal role in delivering scalable, robust, and innovative data solutions that meet organizational goals.Key ResponsibilitiesDesign and develop end-to-end data architecture solutions on the Databricks platform.Collaborate with stakeholders to understand business needs and translate them into technical requirements.Lead the implementation of data pipelines and workflows using Databricks and other data engineering tools.Optimize performance of Databricks notebooks, clusters, and jobs for efficiency and cost-effectiveness.Integrate Databricks with cloud platforms (e.G., AWS, Azure, Google Cloud) and third-party tools.Implement best practices for data governance, security, and compliance.Drive the adoption of advanced analytics, machine learning, and AI use cases using Databricks.Provide technical leadership, mentoring, and guidance to team members.Monitor and troubleshoot data pipelines, ensuring high availability and reliability.Keep up with the latest Databricks features and updates to recommend improvements.Required QualificationsBachelor’s or master’s degree in computer science, Data Engineering, or a related field.10+ years of experience in big data engineering, architecture, or related field.Strong expertise in Databricks, Spark, and big data technologies.Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud).Proficiency in programming languages such as Python, Scala, or Java.Solid understanding of data modeling, ETL processes, and data warehousing.Experience with CI / CD pipelines and DevOps practices for data engineering.Knowledge of data governance, privacy, and security principles.Excellent problem-solving, communication, and teamwork skills.Preferred QualificationsDatabricks certification (e.G., Databricks Certified Professional).Familiarity with machine learning frameworks and libraries (e.G., MLflow, TensorFlow, PyTorch).Experience with visualization tools such as Power BI, Tableau, or Looker.Knowledge of Kubernetes and containerization for big data workloads.Understanding of streaming data frameworks like Kafka or AWS Kinesis.Seniority levelMid-Senior levelEmployment typeFull-timeJob functionConsultingIndustriesBusiness Consulting and Services and IT Services and IT Consulting#J-18808-Ljbffr