IT engineer Data Lakehouse - Tech Lead job opportunity at Continental.

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Date2025-11-04T04:44:28.330Z bot
Continental IT engineer Data Lakehouse - Tech Lead
Experience: General
Pattern: Full-time
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degreeGeneral
loacation Electronic City Road, Bengaluru, Karnataka, India
loacation Electronic Cit..........India
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Job Description* Govern the enterprise-wide standards for data & analytics modeling and performance within the Databricks Lakehouse. * Drive consistency and reuse of core data & analytics artifacts and ensure scalable integration across all business domains. * Provide expert consulting, quality assurance, and enablement for data engineering and data science teams. * Act as a design authority for data warehouse, semantic modeling, and advanced analytics integration.* Acts as the senior engineering point of contact for the lakehouse layer across global teams. * Coordinates with 25+ data engineering and data science professionals across domains and geographies. * Collaborates closely with platform architects, data scientists, governance teams, and functional IT globally.Main Tasks: • Define enterprise 3NF and warehouse modeling standards. • Maintain and review enterprise-wide data & analytics models and shared artifacts. • Align naming conventions and metadata handling with governance standards.• Guide partitioning, indexing, and performance tuning. • Enable, steer and optimize semantic integration with Power BI, live tabular exploration and other tools. • Own common functions, e.g. FX conversion, BOM logic, time-slicing.• Review and approve core components for quality and reusability. • Provide support on high-performance or high-complexity challenges. • Align lakehouse implementation with architectural decisions.• Collaborate with data science and AI teams on model deployment. • Ensure seamless integration of ML/AI pipelines into the lakehouse. • Support LLM and external API integration patterns.• Build and maintain shared libraries and data engineering templates.  • Coach junior engineers and define TDD and "as-code" standards. • Drive engineering excellence across the community of practice.• Maintain architectural blueprints, templates, and best practices. • Publish design guidelines and coding standards. • Create re-usable architecture patterns for lakehouse environments.• Monitor usage and implement auto-scaling policies. • Analyze and optimize cluster configurations for cost-efficiency. • Provide cost transparency and usage reporting to stakeholders.    

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