Snowflake Data Architect

Experience Details:

• 14+ years of overall experience in Big Data, Snowflake, Data Warehousing, and Data Architecture.
• Minimum 11+ years of experience in architecture and solutioning across Snowflake, AWS, Big Data, and Data Warehousing.
• Strong experience in architecting and implementing large-scale data solutions on cloud platforms, with AWS preferred.
• Proven experience in leading end-to-end architecture, solution design, POCs, technical decision-making, and implementation.

Technical Skills & Expertise

Snowflake & Data Architecture

• Strong expertise in Snowflake architecture, data warehousing, data modelling, performance optimization, and cost optimization.
• Hands-on experience with Snowflake features and capabilities, including Snowflake Cortex and Generative AI.
• Ability to evaluate and leverage newly introduced Snowflake features to deliver modern and efficient solutions.
• Strong understanding of secure data sharing, Snowflake Data Clean Rooms, data security, and secure coding standards.
• Experience in designing and implementing frameworks to reduce estimation, development effort, and cost for repetitive data ingestion/extraction activities.
• Ability to identify innovative approaches and recommend solutions aligned with customer standards and business requirements.

AWS & Cloud

• Strong hands-on experience with the AWS ecosystem, including:

• Amazon S3

• EC2

• AWS Lambda

• Other relevant AWS data and analytics services

• Strong understanding of cloud implementation, cloud architecture, scalability, availability, security, and cost optimization.

• Experience in designing cloud-based data platforms and solutions.

Big Data & Data Engineering

• Strong experience with Apache Spark and PySpark.

• Experience working with Big Data technologies and ecosystems, including:

• Hadoop

• Hive

• HBase

• Pig

• Kafka

• NiFi

• Airflow

• Good understanding of batch and real-time data ingestion architectures.

• Experience in designing data pipelines for source, refined, and centrally published datasets.

• Experience with parallel processing and large-scale data processing frameworks.

Database & Programming

• Strong knowledge of:

• SQL

• Relational and distributed databases

• Linux/Unix environments

• Java

• Database and data-centre setup concepts

• Experience in designing database objects, data models, clustering, and compute/storage requirements.

Data Governance & Security

• Strong understanding of data governance, data security, privacy, and compliance, including GDPR.
• Experience in implementing security and governance controls across the data ecosystem.
• Understanding of secure coding practices and secure data-sharing mechanisms.

Data Migration & Integration

• Experience in data migration from legacy systems to modern cloud/data platforms.
• Experience with data ingestion, extraction, transformation, integration, and publication frameworks.
• Exposure to both batch and real-time data integration.

BI & Testing

• Knowledge of BI/reporting tools and frameworks is an advantage.
• Knowledge of performance and testing tools such as JMeter is desirable.

Architecture & Documentation

• Proficient in preparing and reviewing technical architecture documentation, including:

• HLD High-Level Design

• LLD – Low-Level Design

• UML

• Solution Architecture Documents

• Strong experience in translating business and technical requirements into scalable architecture and solution designs.