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We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Staff Analytics Engineer
Location
United States
Posted
100 days ago
Salary
0
No structured requirement data.
Job Description
Staff Analytics Engineer
Jobgether
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role is responsible for leading the technical strategy and execution of a complex data ecosystem, transforming legacy systems into a modular, high-performance architecture. You will architect scalable solutions, define data standards, and optimize performance across analytics pipelines. - Lead the migration of large-scale, legacy data models into a modular Medallion Architecture to improve maintainability and scalability. - Define and enforce standards for data contracts, naming conventions, testing frameworks, and governance across analytics projects. - Optimize performance and efficiency in data warehouses, workflows, and DAGs to reduce costs and improve query speed. - Mentor and provide technical guidance to Senior and Mid-level engineers, elevating the overall technical bar. - Collaborate with business stakeholders and analysts to ensure infrastructure supports both immediate analytics needs and long-term strategic growth. - Drive architectural vision, identify systemic inefficiencies, and implement elegant solutions that balance simplicity and scalability. Qualifications - 8+ years of experience in analytics engineering or data architecture, with a strong track record of migrating complex legacy environments. - Expert-level knowledge of dbt, including multi-project dependencies and refactoring large-scale pipelines without breaking downstream systems. - Advanced proficiency in Python for data operations, Airflow for orchestration, and version control/CI-CD practices. - Strong architectural vision with the ability to design simple, elegant abstractions from complex data environments. - Proven ability to influence cross-functional teams and stakeholders without direct authority. - Experience with performance optimization, scalability, and governance in data warehouse environments (e.g., Snowflake). - Excellent problem-solving, mentoring, and collaboration skills in a fast-paced, mission-driven environment. Benefits - Competitive base salary range of $140,000—$192,000 USD, with potential for equity and variable pay. - Health, dental, and vision benefits with additional wellness resources. - Flexible hybrid or fully remote work arrangements, with resources to set up a productive home office. - Opportunities to work on high-impact analytics projects in a fast-growing, data-driven platform. - Mentorship and professional growth in advanced data engineering practices and architecture. - Inclusive, collaborative environment emphasizing innovation, quality, and long-term infrastructure health.
Job Requirements
- 8+ years of experience in analytics engineering or data architecture, with a strong track record of migrating complex legacy environments.
- Expert-level knowledge of dbt, including multi-project dependencies and refactoring large-scale pipelines without breaking downstream systems.
- Advanced proficiency in Python for data operations, Airflow for orchestration, and version control/CI-CD practices.
- Strong architectural vision with the ability to design simple, elegant abstractions from complex data environments.
- Proven ability to influence cross-functional teams and stakeholders without direct authority.
- Experience with performance optimization, scalability, and governance in data warehouse environments (e.g., Snowflake).
- Excellent problem-solving, mentoring, and collaboration skills in a fast-paced, mission-driven environment.
Benefits
- Competitive base salary range of $140,000—$192,000 USD, with potential for equity and variable pay.
- Health, dental, and vision benefits with additional wellness resources.
- Flexible hybrid or fully remote work arrangements, with resources to set up a productive home office.
- Opportunities to work on high-impact analytics projects in a fast-growing, data-driven platform.
- Mentorship and professional growth in advanced data engineering practices and architecture.
- Inclusive, collaborative environment emphasizing innovation, quality, and long-term infrastructure health.
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