Architect

Key Responsibilities

• Data Pipeline Development: Design, develop, and maintain efficient, reliable, and reusable ETL/ELT pipelines using DBT, Snowflake, and related technologies.
• Data Modeling: Build and optimize data models (star, snowflake schemas) to support analytical and reporting use cases, ensuring data quality, accuracy, and performance.
• Data Integration: Integrate data from multiple sources (APIs, databases, SaaS platforms, cloud storage) into Snowflake using modern data ingestion tools and frameworks.
• Performance Optimization: Tune SQL queries, manage compute resources, and optimize Snowflake performance for scalability and cost efficiency.
• Data Governance & Quality: Implement data validation, testing, and monitoring processes to ensure high data quality and consistency across environments.
• Collaboration: Partner with data analysts, data scientists, and business teams to understand requirements, define transformations, and deliver high-quality datasets.
• Automation & CI/CD: Contribute to automation, version control, and deployment best practices using Git, CI/CD pipelines, and DBT Cloud (or similar).
• Documentation: Maintain clear, comprehensive documentation for pipelines, data models, and workflows.
  
  

Required Skills & Qualifications

• Education: Bachelor's degree in computer science, Information Technology, Engineering, or related field.
• Experience: 10-15 years in data engineering, with at least 5+ years of hands-on experience in Snowflake and DBT.
• Technical Expertise: o Strong SQL skills and experience in building complex transformations.
• Proficiency in Snowflake architecture (warehouses, micro-partitioning, clustering, query optimization, etc.). o Deep understanding of DBT (models, macros, testing, documentation, version control). o Experience with cloud platforms such as AWS, Azure, or GCP (e.g., S3, Lambda, Cloud Storage). o Familiarity with Python or Scala for data engineering workflows. o Knowledge of orchestration tools such as Airflow, Dagster, or Prefect. o Experience with Git, CI/CD, and deployment automation.
  
  

Preferred Skills

• Exposure to data warehousing concepts, data lake architectures, and real-time streaming (Kafka, Kinesis, etc.).
• Familiarity with BI tools such as Looker, Power BI, or Tableau.
• Knowledge of data governance, security, and compliance standards (GDPR, HIPAA, etc.).
• Experience working in an Agile environment.