Description:
The Data Architect role offers the successful candidate the opportunity to pioneer the adoption of generative AI in design, development and migration of data applications. This is a hands-on technical role involving deep collaboration with both product & engineering team and its customers & partners. The role drives the maturation and adoption of Client redefined software design lifecycle amongst both cloud data warehouse partners and customers.
Responsibilities
- Identify and quantify customer business requirements across the product’s use-cases.
- Design Client generative AI powered software design lifecycle solutions for the identified use-cases across leading cloud data warehouses like Snowflake and Databricks.
- Architect, implement, and optimize automated data pipelines, ETL processes, model workflow and data warehousing solutions.
- Design, document and advocate best practices for data architecture, AI modeling, and data integration for accelerated adoption of Client solutions.
- Conduct technical assessments, develop proofs-of-value, and present automated solutions for driving optimized paths of product adoption within customers.
- Continue to build deep subject-matter expertise in latest industry trends and advancements in cloud data platforms, code generation LLMs, text-to-query and related technologies.
- Architect and implement security, compliance, and data governance standards in all Client solutions.
About you
- Graduate education background in computer science or information technology.
- Minimum of 5 years of experience in a Data Architect or Solutions Architect role with a focus on implementing cloud data warehouse (e.g. Snowflake, Databricks) solutions.
- Enterprise customer facing experience in driving large scale cloud data warehouse implementations/migrations is strongly preferable.
- Strong expertise in data warehousing, ETL processes, AI modeling, and data integration techniques.
- Proficiency in programming languages such as SQL, Python, and Scala.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Deep understanding of data modeling, AI algorithms (e.g. forecasting, anomaly detection etc.), data governance, and data security principles.
- Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Strong communication and presentation skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
- Relevant certifications in Snowflake, Databricks, AI, or cloud platforms are a plus.