Staff Analytics Engineer

Summary

Join Docker for a whale of a ride! As a Senior Analytics Engineer, you will collaborate with cross-functional teams to design, build, and optimize complex data solutions, driving our organization’s data-driven decision-making efforts.

Requirements

• 5+ years of experience in data engineering or analytics engineering roles, with a proven track record of leading complex data projects and initiatives
• Deep expertise in SQL, DBT, and data modeling, with a strong understanding of data pipeline design, ETL processes, and data warehousing
• Proficiency in software engineering principles, including CI/CD pipelines, version control (e.g., Git), and scripting languages (e.g., Python)
• Hands-on experience with tools like Snowflake, DBT, and Looker. Familiarity with additional tools and platforms (e.g., AWS, Kubernetes) is a plus
• Strong analytical and problem-solving skills, with the ability to diagnose and resolve complex technical issues related to data infrastructure
• Demonstrated ability to mentor and lead junior engineers, with a focus on fostering a collaborative and high-performance team environment
• Excellent communication skills, with the ability to clearly and concisely convey complex technical concepts to both technical and non-technical stakeholders
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field

Responsibilities

• Design, develop, and maintain highly scalable and efficient data pipelines, ensuring timely and accurate collection, transformation, and integration of data from various sources
• Architect and implement robust data models and data warehousing solutions that enable efficient storage, retrieval, and analysis of large, complex datasets
• Work closely with data scientists, analysts, and business stakeholders to understand data requirements, translating them into actionable data models and insights
• Implement and oversee rigorous data validation, cleansing, and error-handling mechanisms to maintain high data quality and reliability
• Continuously monitor and optimize data pipeline performance, identifying and resolving bottlenecks and inefficiencies to maintain optimal system responsiveness
• Provide guidance and mentorship to junior analytics engineers, fostering a collaborative and learning-oriented environment
• Contribute to the strategic direction of data initiatives, staying abreast of industry best practices, emerging technologies, and trends in data engineering and analytics
• Build and maintain user-facing documentation for key processes, metrics, and data models to enhance the data-driven culture within the organization

Benefits

• Freedom & flexibility; fit your work around your life
• Home office setup; we want you comfortable while you work
• 16 weeks of paid Parental leave
• Technology stipend equivalent to $100 net/month
• PTO plan that encourages you to take time to do the things you enjoy
• Quarterly, company-wide hackathons
• Training stipend for conferences, courses and classes
• Equity; we are a growing start-up and want all employees to have a share in the success of the company
• Docker Swag