We are looking for a seasoned Data Architect with a proven track record of delivering highly scalable Data Platform.

Responsibilities :

- Ability to understand the business requirements and to decompose for further analysis

- Proven track record in architecting performant and highly-scalable Data Platform

- Ability to understand customer's business outcomes and to guide the customer through a Data workshop

- The aptitude and attitude needed to be a Trusted Advisor to the customer

- Understanding of various architectural patterns in Big Data

- Ability to operate in an agile environment

- Ability to actively seek out optimization approaches for Data Platform

- Ability to understand and articulate a problem

- Proven track record on Presales engagements

Required Skills and Attributes :

- Data Modeling : Design and develop conceptual, logical, and physical data models that define data storage, processing, and access patterns. Ensure models support current and future business needs and align with data governance standards.

- Data Integration : Architect solutions to integrate data from diverse sources, enabling unified and consistent data access across the organization. Ensure seamless data flow between systems including legacy and modern platforms.

- Data Warehouse and Data Lake Architecture : Design scalable, efficient, and secure data warehouse and data lake/lakehouse architectures that support analytics and reporting requirements. Implement best practices in dimensional and normalized modeling for data warehouses.

- Cloud Data Platform Modernization : Lead migration and modernization efforts from legacy on-premises databases (e.g., Informix) to cloud-native or hybrid cloud platforms such as AWS, Azure, or Google Cloud. Develop detailed migration plans ensuring data integrity, security, and minimal downtime.

- Proficiency in Databricks/Snowflake : Utilize Databricks or Snowflake for building modern data platforms, including data processing, storage, and analytics. Optimize performance and scalability of these platforms.

- Relational and Non-Relational Database Expertise : Manage and optimize relational databases (SQL Server, Oracle, MySQL) and NoSQL databases (DynamoDB, CosmosDB, DocumentDB) as part of the data architecture.

- Data Security and Governance : Establish and enforce data governance frameworks, data quality standards, and security policies to ensure compliance and protect sensitive information.

- Performance Optimization : Monitor and tune database and data platform performance to meet business SLAs and optimize costs, including scaling and replication strategies in cloud environments.

- Collaboration and Stakeholder Engagement : Work closely with business analysts, data engineers, data scientists, and IT teams to align data architecture with organizational goals and ensure smooth implementation.

- Technology Selection and Strategy : Evaluate and select appropriate technologies and tools for data storage, processing, and analytics that align with business needs and future scalability.

- Documentation and Continuous Improvement : Maintain architecture design documents, update standards, and stay current with emerging data technologies to continuously improve data solutions.

- Experience with Lakehouse Architectures : Knowledge of combining data lake flexibility with data warehouse performance in lakehouse solutions to support diverse analytics workloads.

- ETL/ELT Design and Automation : Design and implement efficient extract-transform-load processes and automation for data ingestion and processing pipelines.

- Cloud Certifications : Certifications in AWS, Microsoft Azure, or Google Cloud Platform that validate cloud architecture skills and best practices.

Good to have :

- Cost-Benefit Analysis and ROI Assessment : Ability to assess financial and operational impacts of data platform choices and migrations to optimize investment.

- Leadership and Project Management : Lead teams and projects involving multiple stakeholders, manage deadlines, and facilitate testing and deployment phases.

- Data Visualization and Reporting : Support creation of dashboards and reports that provide actionable insights from data architectures.

- Security Implementation : Hands-on experience with implementing advanced security measures such as threat-driven security settings, SSL certificates, and access controls.

- Support for Multi-Cloud and Hybrid Environments : Design architectures that function seamlessly across multiple cloud providers and on-premises systems