We are seeking a seasoned Data Architect with extensive experience designing and optimizing enterprise-grade data solutions. This role is integral to shaping the data strategy and architecture of large-scale systems supporting critical business initiatives. You will be responsible for leading architectural decision-making for modern data lakehouse environments, ensuring scalability, reliability, and compliance across a complex data ecosystem.

Key Responsibilities :

Enterprise Data Architecture :

- Design, develop, and implement data architecture strategies that support business requirements across structured, semi-structured, and unstructured data.

Data Modeling :

- Build conceptual, logical, and physical data models using tools like Erwin or IBM InfoSphere Data Architect. Ensure data models align with enterprise standards and support performance and scalability needs.

Data Lakehouse Design :

- Architect and implement data lakehouse solutions leveraging platforms like Databricks. Drive best practices for data ingestion, storage, transformation, and consumption.

ETL and Data Integration :

- Lead design and optimization of ETL pipelines and data workflows, ensuring robust data movement, cleansing, and enrichment processes.

Data Governance & Compliance :

- Establish data governance frameworks encompassing metadata management, data lineage, data quality, and compliance with regulations such as GDPR and HIPAA.

Technology Enablement :

- Work across traditional RDBMS, NoSQL, and modern cloud-native data platforms (Azure Data Services, Google Cloud Platform). Provide architectural guidance on platform selection, integration patterns, and performance tuning.

Visualization & Reporting :

- Collaborate with BI teams to define semantic layers and optimize performance of dashboards using tools like Power BI.

Cross-functional Leadership :

- Partner with product owners, business analysts, data engineers, and software developers to ensure that data architecture aligns with business goals. Provide technical leadership and mentorship across teams.

Technical Skills & Qualifications :

- Minimum 12 years of experience in enterprise data architecture and data modeling.

- Expertise in data modeling tools (e.g., Erwin, IBM InfoSphere Data Architect).

- Strong hands-on experience with modern data lakehouse platforms (Databricks preferred).

- Deep understanding of ETL/ELT pipelines, big data processing, and real-time streaming data architectures.

- Proficiency with SQL and NoSQL database technologies.

- Familiarity with transactional database design and operational data stores.

- Experience with cloud-native data ecosystems (Azure Data Lake, Synapse, GCP BigQuery, etc.).

- Strong understanding of metadata and master data management practices.

- Knowledge of data privacy and compliance frameworks such as GDPR, HIPAA, and data classification models.

- Proficiency in visualization and reporting platforms such as Power BI.