Analytics Engineering Manager
New
J
JobgetherFintech
Opportunity to work remotely within the United States.Full-TimeManager
SalaryCompetitive base salary combined with stock options.
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Job Details
- Experience
- 7+ years of professional experience in data engineering, analytics engineering, business intelligence, or a closely related field.
- Required Skills
- SQLCloud ComputingPeople ManagementData engineeringData modelingdbtDatabricks
Requirements
- 7+ years of professional experience in data engineering, analytics engineering, business intelligence, or a closely related field.
- At least 2+ years of experience in technical leadership or people management.
- Advanced proficiency in SQL, Databricks, and dbt.
- Strong experience architecting, developing, and scaling data transformation pipelines within modern cloud environments.
- Deep understanding of analytics engineering best practices, including data modeling, testing, documentation, governance, and data quality.
- Proven ability to collaborate effectively with Product, Engineering, Marketing, Growth, and Operations stakeholders.
- Strong technical judgment and the ability to balance long-term architecture with immediate business priorities.
- Excellent communication and stakeholder management skills.
- Highly proactive, execution-oriented mindset with a strong sense of ownership and urgency.
Responsibilities
- Lead, mentor, and develop a high-performing team of analytics engineers, fostering technical excellence, accountability, collaboration, and continuous growth.
- Own the delivery of robust data pipelines, analytical models, and reporting solutions that turn raw data into reliable, actionable insights.
- Partner closely with Product, Engineering, Growth, Marketing, and Operations teams to understand business needs and deliver scalable data solutions.
- Establish and champion data modeling, testing, documentation, governance, and quality standards across the organization.
- Drive the design, architecture, optimization, reliability, and scalability of the analytics and data transformation infrastructure.
- Use advanced SQL, Databricks, dbt, and modern cloud data practices to support efficient and maintainable analytics workflows.
- Prioritize analytics projects and manage delivery across multiple initiatives, balancing business impact, technical requirements, resources, and timelines.
- Communicate project progress, priorities, risks, and outcomes clearly to technical and non-technical stakeholders.
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