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High-Level Data Architect
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As a key contributor to our engineering group, we are seeking a skilled Platform Engineer with expertise in designing and developing scalable data pipelines and platform services using Python, Apache Spark, and Databricks.We are looking for a seasoned engineer who can design and develop maintainable data pipelines and platform services using Python, Apache Spark, and Databricks.The ideal candidate will have hands-on experience with notebook-based workflows (Jupyter, Databricks, etc.) for data processing, analysis, and automation.A strong understanding of data integration workflows and reusable components for ingestion, transformation, and orchestration is required.The successful candidate will be responsible for deploying and managing workloads on Kubernetes, ensuring scalability and reliability.They should also have experience with cloud-native solutions on AWS, GCP, or Azure.Collaboration with data science, application, and platform teams to deliver efficient and robust data services is essential.The ideal candidate will have strong experience in Python for data engineering, scripting, and automation. They should have a solid understanding of Apache Spark and distributed data processing. Additionally, hands-on experience with Kubernetes for container orchestration, workload deployments, and scaling is necessary.This role requires a detail-oriented individual who can work independently and as part of a team to achieve project goals. The successful candidate will have excellent communication and problem-solving skills.
