Lead Data Engineer

Role: Lead Data Engineer
Location: New York, NY 10118 - onsite 4x a week
Role: 3-6 months contract to hire

JOB Description:

This critical role partners with internal stakeholders, and technical resources to lead the design, implementation, and long-term management of the organization s Snowflake data platform. The Senior Data Engineer will be responsible for leading data integration for Snowflake, building a scalable data infrastructure, and ensuring high performance and integration with future data sources including warehouses, third-party logistics, retail systems, and e-commerce platforms. This role is an individual contributor role with added responsibility for leading the technical design strategy, transforming the way the organization leverages data for business intelligence.

Key Essential Responsibilities:

• Platform Architecture & Development: Responsible for the design, development and architecture of the Snowflake data platform to meet current and future business requirements, ensuring scalability, performance, and security.
• Data Integration: Lead and develop the data integration work from legacy systems into Snowflake, developing a robust data migration plan that ensures data consistency, security, and reliability across all environments (development, testing, staging, and production).
• Data Modeling and ETL Design: Lead and develop ETL and data modeling strategies using tools such as DBT/Coalesce to build efficient, reusable data pipelines and structures for analytics and reporting.
• Reporting Integration: Ensure seamless integration with reporting tools like Sigma and Power BI, enabling business teams to derive insights and make data-driven decisions.
• Performance Tuning and Optimization: Lead the Snowflake optimization strategies, including query tuning, clustering, and load balancing, to maintain high performance and efficient data storage.
• ELT/ETL Development: Develop, mentor and lead a team of data engineers, fostering a culture of continuous improvement and technical excellence.
• Data Quality and Governance: Establish and enforce data quality and governance standards, ensuring data integrity and compliance across the Snowflake platform.
• Continuous Improvement: Identify opportunities for automation and process optimization to enhance data engineering efficiency and scalability.
• Security and Compliance: Implement robust security practices within Snowflake, including role-based access, encryption, and other data privacy measures to ensure compliance with company policies.

Qualifications:

• Education: Bachelor's degree in computer science, Data Engineering, or a related field required; advanced degrees and Snowflake certifications are a plus.
• Experience: 8+ years in data engineering or platform engineering, with at least 3 years of Snowflake experience. Experience with legacy data system migrations and cloud data platforms is highly preferred.
• Technical Expertise: Strong expertise in Snowflake, including Virtual Warehouses, Time Travel, and best practices for data modeling and security.
• Programming and Data Integration Skills: Proficiency in SQL and Python (or similar scripting language) and experience with ETL/ELT tools.

• Snowflake development
• Azure ecosystem experience
• Hands on experience with multiple ingestion patterns
• Azure Data Factory for batch ingestion
• Event based ingestion using Event Grid/Event Hubs

• Cloud Infrastructure Knowledge: Experience with cloud platforms (Azure, AWS or Google Cloud Platform) and integrating hybrid data environments.

Knowledge and Skill Requirements/Specialized Courses and Training:

• Data Security and Compliance: Solid understanding of data governance frameworks and data privacy standards.
• Platform Optimization and Monitoring: Experience with Snowflake optimization techniques and platform monitoring.
• Cross-Functional Collaboration: Skilled in managing cross-functional stakeholders to align on data strategies and reporting needs.

Desired Skills:

• Snowflake certification (e.g., SnowPro Advanced).
• Experience with CI/CD practices and infrastructure as code (IaC) tools like Terraform or GitHub Actions.
• Experience with DBT and Apache Airflow or Coalesce
• Familiarity with retail or wholesale data processes, ideally within the fashion or consumer goods industry.

Thanks,
Fredric

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