Data Architect

Accountabilities

• Design and implement scalable data architecture solutions across cloud and hybrid environments.
• Leverage Databricks for data processing, analytics, and machine learning workflows.
• Collaborate with engineering and business teams to translate requirements into data models and pipelines.
• Orchestrate and monitor ETL workflows using Apache Airflow.
• Ensure data security, compliance, and governance standards are met.
• Optimize data storage, processing, and querying for performance and cost efficiency.
• Provide technical leadership and mentor teams on data best practices.

• 10+ years in data architecture and analytics.
• Strong expertise in Databricks.
• Proficiency with at least one cloud platform (AWS, Azure, or GCP) and integrating Databricks with them.
• Solid understanding of data engineering, ETL, and data modelling principles.
• Advanced SQL for querying, transformation, and analysis.
• Proficiency in Python for scripting, automation, and data manipulation.
• Strong hands-on experience with Apache Airflow for workflow orchestration.
• Familiarity with big data technologies (Spark, Hadoop, etc.).
• Knowledge of data warehousing concepts and best practices.
• Proficiency in version control systems (Git).
• Excellent communication and collaboration skills.

Desirable Skills / Experience

• Relevant certifications in Databricks and cloud platforms.
• Experience defining data governance frameworks.
• Exposure to advanced ML/AI use cases with Databricks.
• Hands-on work with containerization/orchestration tools (Docker, Kubernetes).