Data Architect

We are looking for a Data Architect with a strong background in data engineering & cloud data platforms. The ideal candidate will design and implement scalable data architectures that power enterprise analytics AI/ML and GenAI solutions - ensuring data availability quality and governance across the organization.

Key Responsibilities:

Data Architecture & Strategy

• Design & Architecture: Design and implement robust scalable and optimized data engineering solutions on the Databricks platform. Architect data pipelines that scale efficiently and reliably.
• Data Pipeline Development: Develop ETL/ELT pipelines leveraging Databricks notebooks Delta Lake Snowflake tech stack Azure Data Factory etc.
• Cloud Integration: Work closely with cloud platforms like Azure AWS or GCP to integrate Databricks or Snowflake with data storage (e.g. ADLS S3 etc.) databases and other services.
• Performance Optimization: Optimize the performance of data workflows by tuning Databricks clusters improving query performance and identifying bottlenecks in data processing.
• Collaboration: Collaborate with data scientists analysts and business stakeholders to understand business requirements and translate them into scalable data solutions.
• Data Governance & Security: Ensure best practices for data security governance and compliance when working with sensitive or large datasets.
• Automation & Monitoring: Automate data pipeline deployments and create monitoring dashboards for ongoing performance checks.
• Continuous Improvement: Stay up to date with the latest Databricks features and Snowflake eco system best practices to continuously improve existing systems and processes.

Required Skills & Experience:

• 11 years of experience in Data Architecture / Data Engineering roles.
• For Last 3 Years working as Data Architect Role - mandatory
• Expert in Azure Data Factory
• Databricks
• Proven expertise in data modeling ETL/ELT design and cloud-based data solutions (AWS Redshift Snowflake BigQuery or Synapse).
• Hands-on experience with data pipeline orchestration tools (Airflow DBT Azure Data Factory etc.).
• Proficiency in Python SQL and Spark for data processing and integration.
• Experience with API integrations and data APIs for AI systems.
• Excellent communication and stakeholder management skills.