Docker, Inc · 2 days ago

Staff Analytics Engineer

United States

Full-time

Remote

Senior Level, Lead/Staff

5+ years exp

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Comp. & Benefits

No H1B

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Responsibilities

Data Pipeline Leadership: Design, develop, and maintain highly scalable and efficient data pipelines, ensuring timely and accurate collection, transformation, and integration of data from various sources.

Advanced Data Modeling: Architect and implement robust data models and data warehousing solutions that enable efficient storage, retrieval, and analysis of large, complex datasets.

Cross-Functional Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data requirements, translating them into actionable data models and insights.

Data Quality Assurance: Implement and oversee rigorous data validation, cleansing, and error-handling mechanisms to maintain high data quality and reliability.

Performance Optimization: Continuously monitor and optimize data pipeline performance, identifying and resolving bottlenecks and inefficiencies to maintain optimal system responsiveness.

Mentorship and Leadership: Provide guidance and mentorship to junior analytics engineers, fostering a collaborative and learning-oriented environment.

Strategic Contribution: Contribute to the strategic direction of data initiatives, staying abreast of industry best practices, emerging technologies, and trends in data engineering and analytics.

Documentation & Knowledge Sharing: Build and maintain user-facing documentation for key processes, metrics, and data models to enhance the data-driven culture within the organization.

Tool and Technology Expertise: Serve as a key expert in tools such as Snowflake, DBT, and Looker, ensuring they are leveraged effectively to meet business needs.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data EngineeringData ModelingSQLDBTData WarehousingETL ProcessesSnowflakeLookerCI/CD PipelinesGitPythonAWSKubernetesTechnical Leadership

Required

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.

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.