Snowflake AI
Job Requirements
Data Architecture Design: Define and design enterprise-wide data architecture, including data models, data flows, and integration frameworks across multiple systems and domains. Cloud Data Platform Leadership: Architect modern data platforms using cloud technologies such as AWS, Azure, or GCP, leveraging services like Snowflake, Redshift, Databricks, or Synapse. Data Modeling: Develop conceptual, logical, and physical data models for operational and analytical systems, ensuring consistency, scalability, and reusability.Data Integration: Design and oversee data ingestion,transformation, and orchestration processes using tools such as Informatica, Talend, ADF, DBT, Airflow, or Glue.Data Governance & Quality: Establish data governance frameworks, metadata management, and data quality standards to ensure data reliability and compliance. Collaboration & Stakeholder Management: Work closely with business leaders, data engineers, and analysts to translate business needs into scalable data solutions.Performance & Optimization:Ensure high performance and cost efficiency of data systems through optimization of data storage, partitioning, indexing, and query performance. Security & Compliance: Define data security, privacy, and compliance standards aligned with organizational and regulatory requirements (e.g., GDPR, HIPAA).Technology Evaluation:Stay up to date with emerging data technologies, frameworks, and best practices; recommend tools and architectural improvements.Mentorship: Guide and mentor data engineers, modelers, and analysts in implementing architectural standards and best practices. Required Skills & Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. Experience: 10–15 years in data management, including 5+ years in data architecture roles. Technical Expertise: Deep understanding of data modeling (OLTP, OLAP, dimensional, and data vault). Strong experience in SQL, Python, or Scala for data manipulation and design. Expertise in one or more cloud data platforms: Snowflake, Azure Synapse, AWS Redshift, Databricks, or Google BigQuery. Experience with ETL/ELT tools: Informatica, Talend, ADF, DBT, Glue, Airflow, etc. Familiarity with data governance tools (e.g., Collibra, Alation, Informatica EDC). Strong understanding of data lake, data warehouse, and data mesh concepts. Knowledge of API-based integration, streaming data (Kafka, Kinesis), and real-time analytics.
Work Experience
10-15Years
Data Architecture Design: Define and design enterprise-wide data architecture, including data models, data flows, and integration frameworks across multiple systems and domains. Cloud Data Platform Leadership: Architect modern data platforms using cloud technologies such as AWS, Azure, or GCP, leveraging services like Snowflake, Redshift, Databricks, or Synapse. Data Modeling: Develop conceptual, logical, and physical data models for operational and analytical systems, ensuring consistency, scalability, and reusability.Data Integration: Design and oversee data ingestion,transformation, and orchestration processes using tools such as Informatica, Talend, ADF, DBT, Airflow, or Glue.Data Governance & Quality: Establish data governance frameworks, metadata management, and data quality standards to ensure data reliability and compliance. Collaboration & Stakeholder Management: Work closely with business leaders, data engineers, and analysts to translate business needs into scalable data solutions.Performance & Optimization:Ensure high performance and cost efficiency of data systems through optimization of data storage, partitioning, indexing, and query performance. Security & Compliance: Define data security, privacy, and compliance standards aligned with organizational and regulatory requirements (e.g., GDPR, HIPAA).Technology Evaluation:Stay up to date with emerging data technologies, frameworks, and best practices; recommend tools and architectural improvements.Mentorship: Guide and mentor data engineers, modelers, and analysts in implementing architectural standards and best practices. Required Skills & Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. Experience: 10–15 years in data management, including 5+ years in data architecture roles. Technical Expertise: Deep understanding of data modeling (OLTP, OLAP, dimensional, and data vault). Strong experience in SQL, Python, or Scala for data manipulation and design. Expertise in one or more cloud data platforms: Snowflake, Azure Synapse, AWS Redshift, Databricks, or Google BigQuery. Experience with ETL/ELT tools: Informatica, Talend, ADF, DBT, Glue, Airflow, etc. Familiarity with data governance tools (e.g., Collibra, Alation, Informatica EDC). Strong understanding of data lake, data warehouse, and data mesh concepts. Knowledge of API-based integration, streaming data (Kafka, Kinesis), and real-time analytics.
Work Experience
10-15Years
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