Lead Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the technical strategy, architecture, and continuous development of the Snowflake data warehouse, focusing on performance, scalability, security, reliability, and cost-effectiveness.

• Spearhead the design, development, and standardization of scalable ETL/ELT pipelines across various data sources and destinations, with ongoing enhancements towards Azure Data Factory.

• Set and maintain engineering standards for code quality, testing, documentation, version control, deployment, monitoring, and data integrity.

• Direct the design and creation of dimensional data models, including star schemas within a medallion architecture, utilizing dbt, Sigma, and related technologies.

• Collaborate with both technical and business stakeholders to convert data requirements into a prioritized technical roadmap, delivering reliable and reusable data solutions.

• Offer technical expertise through solution design and code reviews; mentor data engineers and analysts.

• Assess and implement tools, methodologies, and process enhancements to boost scalability, reliability, maintainability, and delivery efficiency.

• Lead intricate and on-the-fly data engineering projects from inception to completion while promoting data governance, data literacy, and responsible data practices.

⛳️ Requirements

• A Bachelor's degree in computer science, Information Technology, Engineering, or a closely related field.

• Over 5 years of progressive experience in data engineering, including ownership of complex projects and technical leadership within a contemporary cloud data environment.

• Extensive hands-on experience with Snowflake, covering data warehouse architecture, performance optimization, security and access controls, and cost management.

• Proficient SQL skills.

• Significant experience with a scripting language such as Python for data processing, automation, and troubleshooting tasks.

• Strong background in designing and operating scalable ETL/ELT pipelines, inclusive of orchestration, testing, monitoring, and production support.

• Practical experience with dimensional data modeling, star schema and medallion architectures, and dbt or a comparable transformation framework.

• Familiarity with Azure Data Factory or a similar cloud orchestration platform.

• Proven technical leadership demonstrated through mentoring, design and code reviews, engineering standards, and cross-functional project delivery.

• Excellent communication and prioritization abilities.

🏝️ Benefits

• Equal employment opportunity policy.

• Compensation and training included among protected employment terms and conditions.