Senior Analytics Engineer

Role Overview

• Partner with leadership to drive strategy
• Collaborate with product, operations, and go-to-market leaders to identify the most impactful problems to solve and translate ambiguous business questions into structured analytical frameworks
• Present insights and recommendations to executives and influence strategic decisions across your business unit
• Develop a deep understanding of your domain's challenges, competitive landscape, and growth opportunities
• Own key business metrics and KPIs: defining, instrumenting, and evangelizing them across stakeholders
• Build scalable data infrastructure
• Design, build, and maintain dimensional data models using dbt that serve as the foundation for analytics across your domain
• Create self-service dashboards and reporting tools in Looker/Databricks that empower teams to answer their own questions
• Establish data quality standards and monitoring to ensure stakeholders can trust the data
• Operationalize analytical workflows that scale beyond one-time analyses—building reusable frameworks, automated monitoring, and sustainable data products
• Own high-impact analytical initiatives
• Depending on your business unit, you might: App: Design and analyze growth experiments, build fraud detection models, optimize conversion funnels, and measure product feature adoption to drive user growth and reduce losses API: Create partner health scorecards, analyze API usage patterns, monitor integration reliability, and identify expansion opportunities to strengthen partnerships and operational visibility Carrier Operations: Develop carrier variance and cost attribution models, track SLA performance, identify margin leakage, and improve operational efficiency to recover costs and drive accountability.

Requirements

• 6+ years of experience in analytics engineering, data engineering, data science, product analytics, or related roles with increasing scope and impact
• Expert SQL skills: You write complex, performant queries and deeply understand data modeling principles and optimization techniques
• Analytics engineering expertise: Proven experience building and maintaining data transformation pipelines with dbt or similar tools.
• Data visualization proficiency: Strong experience with Looker or similar BI platforms (Tableau, Mode, Hex) creating dashboards that drive action, not just display data.
• Modern data stack knowledge: Hands-on experience with cloud data warehouses such as Databricks and relevant AWS technologies for big data & analytics.
• Business acumen and communication: You translate technical findings into clear narratives that resonate with both technical and non-technical audiences.
• Proven impact: Clear examples of analytical work that led to measurable business outcomes (e.g revenue growth, cost savings, improved conversion rates, or operational efficiency gains)
• Strategic thinking: You don't just execute requests; you proactively identify opportunities, ask clarifying questions, and recommend the best path forward
• Autonomy and ownership: You're comfortable working independently, managing ambiguity, and seeing complex projects through from conception to adoption.

Tech Stack

• AWS
• Cloud
• SQL
• Tableau

Benefits

• Healthcare coverage for medical, dental, and vision (90% covered by the company, incl. dependents).
• Pets coverage is also available!
• Take-as-much-as-you-need vacation policy & flexible working hours
• One week-long company wide winter slow down
• 3 Volunteer Days Off (VTOs)
• WFH stipend to set up your home office
• Charity donation match up to $100
• Dedicated programs, coaching, tools, and resources for your professional and career growth as well as an individual learning stipend for your personal and focused growth
• Fun team in person time through our Shippos Everywhere program which includes regular team and company off-sites throughout the year as well as local Shippos gatherings.