Data Architect - Databricks

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July 15

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InOrg Global

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Enterprise • SaaS • B2B

InOrg Global is a company specializing in managed services and innovative business strategies. They focus on providing AI/ML services, strategic operations, and workspace management to enhance productivity and efficiency. InOrg offers a unique Build-Operate-Transfer (BOT) model, guiding businesses through design, development, operation, and seamless transition of control to ensure sustained success. The company is dedicated to empowering digital disruptors and optimizing business processes with expertise in global capability centers, helping clients expand their global reach and achieve operational excellence.

51 - 200 employees

🏢 Enterprise

☁️ SaaS

🤝 B2B

📋 Description

• Databricks Solution Architecture: Design and implement scalable, secure, and efficient Databricks solutions that meet client requirements. • Data Engineering: Develop data pipelines, architect data lakes, and implement data warehousing solutions using Databricks. • Data Analytics: Collaborate with data scientists and analysts to develop and deploy machine learning models and analytics solutions on Databricks. • Performance Optimization: Optimize Databricks cluster performance, ensuring efficient resource utilization and cost-effectiveness. • Security and Governance: Implement Databricks security features, ensure data governance, and maintain compliance with industry regulations. • Client Engagement: Work closely with clients to understand their business requirements, provide technical guidance, and deliver high-quality Databricks solutions. • Thought Leadership: Stay up to date with the latest Databricks features, best practices, and industry trends, and share knowledge with the team.

🎯 Requirements

• Databricks Experience: 5+ years of experience working with Databricks, including platform architecture, data engineering, and data analytics. • Technical Skills: Proficiency in languages such as Python, Scala, or Java, and experience with Databricks APIs, Spark, and Delta Lake. • Data Engineering: Strong background in data engineering, including data warehousing, ETL, and data governance. • Leadership: Proven experience leading technical teams, mentoring junior engineers, and driving technical initiatives. • Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal stakeholders. • Good to Have Certifications: Databricks Certified Professional or similar certifications. • Cloud Experience: Experience working with cloud platforms such as AWS, Azure, or GCP. • Machine Learning: Knowledge of machine learning concepts and experience with popular ML libraries