Analytics Engineering Manager

Role Description

We’re looking for an Analytics Engineering Manager to lead the discipline of turning well-modeled data into shared, trusted business understanding. You’ll own the direction and quality of our semantic layer, enterprise reporting, and BI practices while partnering closely with data engineers and stakeholders across Kin’s business.

You’ll own Kin’s semantic layer and BI platform, Looker, and be responsible for the care and evolution of core enterprise reports, as well as the enablement of self-service analytics for smaller and exploratory use cases. You’ll blend your technical leadership, stakeholder collaboration, and hands-on skills to optimize our use of data.

Your Responsibilities

• Provide directional administration of the Looker platform, including permissions, performance considerations, content lifecycle, and development standards
• Partner with teams to align on shared metrics and definitions, and guide them through semantic tradeoffs and definition differences
• Oversee the care, development, and reliability of Kin’s core dashboards and reports
• Partner with data engineers and provide input on dimensional model design and evolution while advocating for best practices that support downstream analytics
• Hire and lead analytics engineers, mentoring them on modeling, semantic design, and stakeholder partnership
• Develop and implement new analytics and reporting solutions

What Success Looks Like

• A clearer direction for Kin’s BI semantic layer, prioritizing simplicity, consistency and long-term durability
• Enhanced self-service through curated datasets, reusable metrics, documentation, and lightweight guardrails
• Improved performance and reliability of enterprise level and self-service reporting and dashboards
• A larger and higher-performing analytics engineering team

Qualifications

• 6–8+ years in analytics engineering, BI engineering, or data modeling roles
• Expert-level SQL and dimensional modeling abilities
• Advanced reasoning related to metrics, definitions, and business meaning
• Proven ability to design simple, durable semantic layers over complex data
• Comfort influencing upstream data design without owning ingestion or platform operations
• Excellent written and verbal communication skills, and ability to align technical and non-technical partners
• High emotional intelligence and empathy when working through differing perspectives
• Demonstrated leadership through mentoring, technical direction-setting, or informal team leadership
• Hands-on experience with modern lakehouse or warehouse platforms (e.g., Databricks) or BI tools (e.g., Looker)

Benefits

• Competitive salary and company equity through Restricted Stock Units (RSUs), granted as part of our standard compensation package
• 401(k) with company match up to 4% of eligible earnings
• Multiple medical plan options, plus dental and vision coverage
• Company-funded HSA contributions (based on medical plan selection)
• Company-paid life insurance and short-term disability
• Employee referral bonuses
• A variety of supplemental benefit options, including long-term disability, critical illness, accident, legal, and pet insurance
• Access to mental health support and confidential counseling resources
• Flexible PTO for exempt employees (most employees take 15–20 days per year), plus 8 company-observed holidays
• Paid parental leave, including up to 14 weeks at 100% pay for birthing parents and 8 weeks at 100% pay for non-birthing parents
• Career mobility and internal growth opportunities across the organization
• Professional development budgets for certifications, conferences, and learning available, subject to management approval