Principal Architect

• Minimum 12+ years of experience as a Principal/Data Architect or similar role, with proven expertise in developing and implementing Data & Analytics strategies.
• Strong understanding and experience with modern data warehouse / Lakehouse solutions like Databricks, Snowflake, Redshift, Synapse, and proficiency in cloud platforms such as AWS, Azure preferred.
• Thorough grasp of data governance and security principles, along with experience in data pipelines and ETL/ELT tools, including Databricks, dbt, Azure Synapse.
• Excellent communication, collaboration, and problem-solving skills are essential.
• Proficiency in Apache Spark, SQL or Python programming languages, knowledge of data patterns, data modelling i.e., Data Vault, and product migration.
• Good to have skills include data visualization using Power BI, Tableau, or Looker, and familiarity with full-stack technologies.
• Familiarity with AI/ML platforms and data preparation for ML initiatives is a plus.

Responsibilities

• Develop and implement a comprehensive data strategy aligned with business objectives.
• Design and architect a modern data platform using cloud technologies (e.g., AWS, Azure, GCP).
• Lead in architecting data landscapes that to reflect data strategies including Data integration, transformation, governance, modelling, BI.
• Build and manage a scalable, secure data warehouse / lakehouse leveraging modern solutions, including implementing data ingestion pipelines from disparate sources.
• Implement CI/CD pipelines for data pipelines and infrastructure using DevOps tools and methodologies.
• Design and implement the framework for data migration from legacy to modern cloud technologies.
• Implement data governance and security best practices to ensure data quality, compliance, and manage metadata.
• Collaborate with our global team to articulate the data & technology and empower our global team to understand the importance of technology on our solutions.
• Collaborate with cross-functional teams to understand data needs, develop data models, and build analytics tools for reporting, analytics, and AI/ML initiatives.
• Effectively communicate technology solutions to clients using clear and concise, non-technical language. Lead the workshop with Clients location to assess the existing data & analytics and provide suitable solutions.
• Design the frameworks and create products for delivery efficiency.
• Stay updated on emerging data technologies, recommend innovations, and evaluate/recommend cloud data platforms.
• Manage and lead a team of data engineers, providing guidance, monitoring end-to-end operational processes, and overseeing the development and maintenance of data pipelines to ensure quality, reliability, security, and scalability.
• Diagnose existing architecture and data maturity, identifying gaps, proposing solutions, and implementing dimensional modelling and business domain conversion/Data Vault design pattern.

Required Skillset:

• ETL or ELT: Databricks / Azure Synapse / dbt / Fivetran (Anyone - Mandatory).
• Data Warehouse / Lakehouse: Databricks / Snowflake / Fabric / Synapse (Anyone - Mandatory)
• Cloud Experience: AWS / Azure / GCP
• SQL and Apache Spark / Python programming languages
• Data Visualization: Power BI / Tableau / Looker. (Anyone-Good to have).
• Version control & Release management: GitHub / Azure DevOps / CI CD pipelines
• Data Governance: Microsoft Purview / Atlan
• Full stack technologies (Good to have)
• Data Modelling: Data Vault, Dimensional modelling
• AI/ML platforms