Experience Required: 10+ years in data architecture, data engineering, enterprise integrations, and analytics platforms.
Locations: Bengaluru / Noida
Summary
The Enterprise Data Architect will serve as the strategic design authority for the organization's modern data ecosystem. This role will partner closely with the Senior Manager of Data Engineering & Integrations to architect scalable, trusted, and wellgoverned data solutions. The ideal candidate will bring deep expertise in Snowflake, data modeling, integration frameworks, BI platforms, and data governance. This position will be responsible for defining enterprise data standards, eliminating redundant structures, improving data integrity, and enabling the business to make data-driven decisions. The role will also support AIenablement initiatives by ensuring data quality, accessibility, and readiness for advanced analytics.
Key Responsibilities
- Define enterprise-wide data architecture standards, frameworks, and best practices.
- Partner with the Senior Manager of Data Engineering & Integrations to design scalable data ecosystems across Snowflake, ADF, Boomi, and BI platforms.
- Architect integrated data models supporting CRM, ERP, Product, Finance, and operational systems.
- Lead data modeling efforts including conceptual, logical, and physical models with strong documentation discipline.
- Identify and eliminate redundant data structures to create a unified, trusted enterprise data layer.
- Ensure data integrity, lineage, governance, and quality through strong architectural controls.
- Collaborate with engineering teams to design Snowflake schemas, pipelines, and performance-optimized structures.
- Work closely with BI teams to design efficient datasets powering Tableau, Power BI, and advanced analytics.
- Support AI/ML enablement by architecting data sets that are accessible, clean, and optimized for modeling.
- Provide architectural oversight for ADF pipelines, Boomi integrations, and cross-system data flows.
- Define metadata, master data, taxonomy, and data stewardship standards.
- Advise stakeholders on data strategy, emerging technologies, and best practices.
Required Qualifications
- 10+ years of experience in data architecture, data engineering, or enterprise analytics environments.
- Strong hands-on expertise with Snowflake including schema design, data modeling, and performance tuning.
- Experience working with Azure Data Factory (ADF), Boomi, and enterprise integration patterns.
- Proficiency in BI platforms such as Tableau and Power BI.
- Deep knowledge of data governance, lineage, metadata, and master data management.
- Experience modernizing BI environments and eliminating redundant data structures.
- Strong understanding of data quality frameworks and best practices.
- Ability to partner with engineering leaders, business stakeholders, and cross-functional teams.
- Experience designing data for AI/ML workloads is preferred.
- Excellent communication and documentation skills.
