Lead Data Engineer

About the Role

Our client is looking for an experienced and driven Lead Data Engineer to establish and manage their data infrastructure within a fully remote setting. This is a critical role focused on designing, building, and maintaining scalable and reliable data pipelines that support analytics, machine learning, and business intelligence initiatives. You will work with a wide range of data sources and technologies, ensuring data quality, availability, and accessibility for the entire organization. The ideal candidate will have a strong background in distributed systems, data warehousing, and cloud-based data platforms, coupled with excellent leadership and communication skills to guide and mentor a remote team. This position offers a fantastic opportunity to shape the data landscape of a forward-thinking company from anywhere.

Key Responsibilities

• Design, develop, and maintain robust, scalable, and high-performance data pipelines and ETL/ELT processes.
• Architect and implement data warehousing solutions and data lake strategies on cloud platforms (e.g., AWS, Azure, GCP).
• Ensure data quality, integrity, and security across all data systems.
• Optimize data infrastructure for performance, cost-efficiency, and reliability.
• Collaborate with data scientists, analysts, and software engineers to understand data needs and deliver solutions.
• Set technical direction and provide architectural guidance for data engineering projects.
• Mentor and lead a team of data engineers, fostering best practices and technical excellence.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 7+ years of experience in data engineering, with a proven track record of building and managing large-scale data systems.
• Strong proficiency in programming languages such as Python, SQL, or Scala.
• Extensive experience with cloud data services (e.g., AWS S3, Redshift, EMR; Azure Data Lake, Synapse; GCP BigQuery, Dataproc).
• Deep understanding of data modeling, data warehousing concepts, and distributed data processing frameworks (e.g., Spark, Hadoop).
• Experience with containerization (Docker) and orchestration (Kubernetes) is a plus.
• Excellent leadership, communication, and problem-solving skills, adapted for a remote work environment.

Benefits

• Highly competitive salary and annual bonus.
• Comprehensive health, dental, and vision insurance.
• Generous stock options or equity grants.
• Remote work flexibility with a stipend for home office setup.
• Professional development budget for conferences and training.
• Significant impact on the company's data strategy and infrastructure.