We are seeking a highly skilled Data Architect with proven expertise in designing, implementing, and optimizing enterprise-scale data solutions leveraging Azure Databricks, Snowflake, and modern data engineering frameworks. The ideal candidate will combine deep technical proficiency with strong architectural vision to drive robust, scalable, and high-performance data lakehouse ecosystems that support advanced analytics, BI, and data science use cases.

You will collaborate closely with data engineers, analysts, business stakeholders, and cross-functional teams to define data architecture strategies, ensure data governance & quality, and deliver solutions aligned with business goals while adhering to industry best practices.

Key Responsibilities :

1. Data Architecture & Design :

- Design, implement, and maintain data lakehouse architectures (Medallion architecture) with Azure Databricks, Unity Catalog, and Delta Live Tables.

- Architect and optimize Snowflake data warehouse solutions, ensuring high performance, scalability, and cost efficiency.

- Develop data models (conceptual, logical, and physical) that support enterprise-level analytics and reporting requirements.

- Apply data classification, taxonomy, ontology, and metadata management best practices to ensure discoverability and consistency.

2. Data Engineering & Pipelines :

- Lead the development of robust ETL/ELT pipelines using Apache Spark/PySpark, DBT, and Databricks SQL.

- Design and implement data ingestion, transformation, and integration solutions from multiple structured and unstructured sources.

- Implement data quality frameworks and monitoring solutions to ensure trusted, accurate, and complete datasets.

3. Governance, Security & Compliance :

- Establish data governance standards, leveraging Unity Catalog for role-based access control, lineage tracking, and audit compliance.

- Ensure compliance with regulatory and organizational data privacy policies.

- Implement master data management (MDM) strategies to ensure a single source of truth.

4. Collaboration & Strategic Alignment :

- Partner with data science teams to enable advanced analytics, ML, and AI workloads.

- Translate complex architectural concepts into clear business-oriented communication for executives and stakeholders.

- Provide technical mentorship and architectural guidance to data engineers and analysts.

5. Technology Evaluation & Innovation :

- Stay abreast of emerging data technologies and evaluate their applicability in solving business problems.

- Champion DevOps, DataOps, and CI/CD best practices for data platforms.

- Drive proof-of-concept initiatives for new tools and methodologies.

Required Qualifications & Experience :

- 9+ years of overall IT experience, with 5+ years in managing data lakehouse environments and modern cloud data platforms.

Strong experience in :

- Azure Databricks (cluster configuration, compute & storage optimization)

- Apache Spark / PySpark

- Databricks SQL, Delta Live Tables, Unity Catalog

- Snowflake Architecture (data sharing, performance tuning, cost optimization)

- Data Modelling (Dimensional, Relational, and NoSQL)

- DBT (Nice-to-have but preferred)

- Strong understanding of SDLC, Agile, DevOps methodologies.

- Bachelors degree in Computer Science, Information Systems, Data Engineering, or related field.