Data Architect

Introduction to the Role

We are seeking an experienced Data Architect with 11 18 years of expertise in data architecture, engineering, and analytics. The role demands deep knowledge of modern data platforms, cloud technologies, and big data frameworks to design scalable, secure, and high-performing data solutions.

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.

Essential Skills / Experience

• 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).