Data Architect

Job Summary We are seeking an experienced Data Architect with strong expertise in Databricks Lakehouse Platform, modern data architectures, cloud technologies, and enterprise data solutions. The ideal candidate will be responsible for designing, implementing, and governing scalable data platforms that support analytics, reporting, AI/ML, and business intelligence initiatives. This role requires deep technical expertise in Databricks, data modeling, cloud data engineering, and architecture best practices. Key Responsibilities Define and implement enterprise-wide data architecture strategies aligned with business objectives. Design scalable and secure data platforms using the Databricks Lakehouse architecture. Architect batch and real-time data ingestion frameworks from multiple source systems. Develop data models, data warehouses, data lakes, and lakehouse solutions. Lead the migration of legacy data platforms to cloud-based modern data architectures. Define data governance, metadata management, data quality, lineage, and security standards. Collaborate with business stakeholders, data engineers, analysts, and data scientists to understand requirements and translate them into technical solutions. Establish architecture frameworks, best practices, and reusable design patterns. Optimize data pipelines and platform performance for scalability and cost efficiency. Support advanced analytics, AI/ML, and GenAI use cases through robust data architecture. Conduct architecture reviews and provide technical guidance to engineering teams. Ensure compliance with enterprise security and regulatory requirements. Required Skills & Qualifications Technical Skills Strong experience in Databricks Lakehouse Platform. Expertise in Apache Spark (PySpark/Scala Spark). Hands-on experience with Delta Lake, Unity Catalog, Delta Live Tables, and Databricks Workflows. Strong understanding of data warehousing and dimensional modeling concepts. Experience with cloud platforms: Microsoft Azure (preferred) AWS GCP Knowledge of: Azure Data Factory (ADF) Azure Synapse Analytics Azure Data Lake Storage (ADLS) Kafka/Event Hubs Expertise in SQL and performance tuning. Experience designing ETL/ELT frameworks and data integration solutions. Understanding of data governance, security, access controls, and compliance frameworks. Experience with DevOps, CI/CD, Infrastructure as Code (Terraform preferred). Exposure to BI tools such as Power BI, Tableau, or Looker. Architecture Expertise Enterprise Data Architecture Lakehouse Architecture Data Mesh / Data Fabric concepts Master Data Management (MDM) Metadata Management Data Governance Real-time Analytics Architecture AI/ML Data Platform Design Experience with Generative AI and LLM-based data solutions. Knowledge of Microsoft Fabric. Experience with Snowflake, BigQuery, or Redshift. Exposure to MLOps frameworks and AI governance. Experience in regulated industries such as Banking, Healthcare, Insurance, or Retail. Success Metrics Delivery of scalable and high-performing data architectures. Reduced data processing costs and improved platform efficiency. Improved data quality, governance, and accessibility. Successful implementation of cloud modernization initiatives. Increased adoption of analytics and AI-driven solutions.