Driving Business Growth through Data Engineering Leadership

7 days ago

Thāne, Maharashtra, India beBeeDataEngineering Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Enterprise Data Architecture Lead

We are seeking an experienced Enterprise Data Architecture Lead to drive the next phase of our data analytics journey. This role involves technical leadership, architecture design, production management, and collaboration with cross-functional teams.

As a key member of our data organization, you will be responsible for designing and implementing multi-layered architectures across cloud, on-premises, and hybrid platforms. You will lead daily processes for efficient and reliable delivery of all programs end-to-end, including oversight of change management for enrichment as per change requests.

  • Design and implement enterprise data architectures that meet business requirements and adhere to industry best practices.
  • Collaborate with governance and stewardship teams to integrate metadata management, lineage mapping, and catalog tools.
  • Develop conceptual, logical, and physical data models using consistent standards, including dimensional, normalized, and denormalized structures for analytical and operational use cases.
  • Provide guidance on data partitioning, indexing, access controls, naming conventions, and performance optimization across multiple platforms.

The ideal candidate will have deep knowledge of architecture patterns and principles, performance tuning, and best practices in data engineering. They will also possess excellent communication and leadership skills to collaborate with analysts, governance leads, engineering teams, and application architects.

This is a unique opportunity to shape our data organization and contribute to our growth strategy. If you are passionate about data engineering and leadership, we encourage you to apply.

Key Responsibilities:
  • Architecture Design and Implementation
  • Production Management and Oversight
  • Metadata Management and Lineage Mapping
  • Data Modeling and Optimization
Requirements:
  • Deep knowledge of data engineering and architecture patterns
  • Experience with cloud, on-premises, and hybrid platforms
  • Strong leadership and communication skills
  • Ability to collaborate with cross-functional teams

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