Snowflake Data Engineer

This role is for one of the Weekday's clients

Snowflake Data Engineer

Snowflake, DBT, ETL processes, and modern Lakehouse architecture

SnapLogic and Python

Requirements

Key Responsibilities

• Data Modeling & Warehousing: Design, implement, and optimize scalable data models and data warehouses using Snowflake to meet analytical and business requirements.
• ETL Development: Build, maintain, and optimize ETL/ELT pipelines with SnapLogic, DBT, and Python, ensuring efficient ingestion and transformation of structured and unstructured data.
• Lakehouse Architecture: Contribute to the development of a modern Lakehouse architecture, enabling unified data storage and advanced analytics.
• Performance Optimization: Monitor, troubleshoot, and fine-tune queries, pipelines, and workflows to ensure high performance and reliability.
• Automation & Integration: Develop reusable frameworks for automation of data workflows, orchestration, and integration with enterprise systems.
• Data Quality & Governance: Implement data validation, error handling, and monitoring mechanisms to ensure data accuracy, integrity, and compliance with governance policies.
• Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions that meet organizational goals.
• Documentation & Best Practices: Maintain clear documentation of designs, workflows, and processes while advocating best practices for data engineering.
  

Required Skills & Qualifications

• 3 - 5 years of professional experience in data engineering or data warehousing roles.
• Strong expertise in Snowflake, including performance tuning, query optimization, and warehouse management.
• Proficiency in DBT (Data Build Tool) for modeling, transformations, and version-controlled data workflows.
• Hands-on experience with ETL/ELT pipeline design using SnapLogic or similar tools.
• Solid understanding of Lakehouse architecture and modern data platform concepts.
• Strong programming skills in Python for data transformation, automation, and API integrations.
• Knowledge of SQL and advanced query writing for analytics and reporting.
• Familiarity with data governance, data security, and compliance frameworks.
• Strong problem-solving skills with the ability to analyze complex data challenges and propose effective solutions.
• Excellent communication and collaboration skills, with the ability to work in cross-functional teams.
  

Preferred Qualifications

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Exposure to orchestration tools such as Airflow, Prefect, or Dagster.
• Familiarity with CI/CD pipelines for data engineering.
• Experience working in an agile, fast-paced product or data-driven organization