Company: Continental

Website: Visit Website

Business Type: Enterprise

Company Type: Product

Business Model: B2B

Funding Stage: Series C

Industry: Retail

Salary Range: ₹ 15-40 Lacs PA

This is the permanent role with a valued client of VidPro.

Mandatory Skills : Enterprise data, Analytics warehouse, lakehouse modeling, ML integration, Data warehouse, Data Lakehouse.

Key Responsibilities

Certifications in Databricks or Microsoft preferred.

- 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.

Required Qualifications

- Degree in Computer Science or related field; certifications in Databricks or Microsoft preferred.

- 6–10 years in data engineering with focus on enterprise data & analytics warehouse, lakehouse modeling, and ML integration.
- Hands-on experience designing large-scale semantic, warehouse, and advanced analytics layers.
- Track record of architectural ownership and peer enablement with diverse teams.
- Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.

📌 Data Engineer (Bengaluru)
🏢 Continental
📍 Bengaluru