Padmi

26-2253 Data Engineer, AI/BI Hyderabad, India

HyderabadPosted 1 month ago
Software engineeringJuniorFull Time; Regular
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Data Engineer AI / BI Artificial Intelligence & Business Intelligence | Data & Analytics Job ID #: 26-2253 Who We Are: Since our inception back in 2006, Navitas has grown to be an industry leader in the digital transformation space, and weve served as trusted advisors supporting our client base within the commercial, federal, and state and local markets. What We Do: At our very core, were a group of problem solvers providing our award-winning technology solutions to drive digital acceleration for our customers With proven solutions, award-winning technologies, and a team of expert problem solvers, Navitas has consistently empowered customers to use technology as a competitive advantage and deliver cutting-edge transformative solutions. Position Overview We are seeking a Databricks Engineer to design, build, and operate a Data & AI platform with a solid foundation in the Medallion Architecture (raw/bronze, curated/silver, and mart/gold layers). This platform will orchestrate complex data workflows and scalable ELT pipelines to integrate data from enterprise systems such as PeopleSoft, D2L, and Salesforce, delivering high-quality, governed data for machine learning, AI/BI, and analytics at scale. You will play a critical role in engineering the infrastructure and workflows that enable seamless data flow across the enterprise, ensure operational excellence, and provide the backbone for strategic decision-making, predictive modeling, and innovation Responsibilities: Data & AI Platform Engineering (Databricks-Centric): - Design, implement, and optimize end-to-end data pipelines on Databricks, following the Medallion Architecture principles. - Build robust and scalable ETL/ELT pipelines using Apache Spark and Delta Lake to transform raw (bronze) data into trusted curated (silver) and analytics-ready (gold) data layers. - Operationalize Databricks Workflows for orchestration, dependency management, and pipeline automation. - Apply schema evolution and data versi .

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