Job Specifications
Profile:
We are seeking an experienced data architecture professional with over 8 years of experience in designing data solutions and architectures. The ideal candidate will possess a deep understanding of data modeling, database design, and data governance principles, along with a strong background in cloud technologies, particularly Azure. Experience with AI and machine learning use cases will be essential.
Responsibilities:
Lead the design and implementation of scalable and resilient data architectures to support analytics, reporting, and AI initiatives, including RAG, Generative AI, and Agentic systems.
Collaborate with cross-functional teams to understand business requirements and translate them into effective data solutions that enable AI capabilities.
Establish and enforce data governance policies to ensure data quality, security, and compliance with relevant regulations.
Develop and maintain data models, including conceptual, logical, and physical models, to support various business applications and analytics needs.
Oversee the integration of data from various sources, ensuring efficient data ingestion, transformation, and storage practices to support AI applications.
Evaluate and recommend data technologies, tools, and platforms that align with the organization's strategic goals, particularly for AI and machine learning.
Mentor and guide junior data professionals, fostering a collaborative and innovative team environment.
Stay abreast of industry trends and advancements in data architecture and AI technologies, continuously improving organizational practices.
Technical Skills
Must Have Skills
Over 8 years of experience in data architecture, data engineering, or related fields, with a focus on cloud technologies and AI use cases.
Extensive experience in data architecture, with a strong understanding of data modeling, database design, and ETL processes.
Proficiency in cloud data services, particularly Azure technologies such as Azure Data Lake, Azure Synapse Analytics, and Azure SQL Database.
Strong knowledge of data governance practices, including data quality, security, and compliance frameworks.
Experience with data integration and transformation tools (e.g., Azure Data Factory, Apache Kafka).
Familiarity with both relational and NoSQL databases, and the ability to design for performance and scalability.
Expertise in data warehousing concepts and architectures, including star and snowflake schemas.
Experience with AI and machine learning frameworks, particularly in implementing RAG and Generative AI solutions.
Understanding of AI model deployment and operationalization, including the use of APIs and microservices.
Microsoft Certified: Azure Solutions Architect Expert
Microsoft Certified: Azure Data Engineer Associate
Nice to have
Experience with big data technologies (e.g., Apache Spark, Hadoop) and data lakes.
Knowledge of data visualization tools (e.g., Power BI) to support reporting and analytics.
Familiarity with natural language processing (NLP) techniques and tools that can be integrated into data architecture for AI applications.
Understanding of regulatory compliance requirements related to data (e.g., GDPR, HIPAA).
DataBricks Data Engineer Associate Certification
Soft Skills:
Strong leadership and collaboration skills to work effectively with cross-functional teams.
Excellent communication skills to articulate complex data and AI concepts to both technical and non-technical stakeholders.
Strategic thinking with the ability to align data architecture with organizational goals.
Problem-solving mindset with a focus on innovation and continuous improvement.
Detail-oriented with a commitment to data quality and governance.
About the Company
HCLTech is a global technology company, home to more than 220,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending Dece...
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