Senior Engineering Manager, Analytics

About the role

Who We Are:

At Emburse, you’ll not just imagine the future – you’ll build it. As a leader in expense intelligence, we are creating a future where technology drives business value and inspires extraordinary results. Our AI-powered platform helps organizations modernize financial operations, increase visibility, and optimize spend across the enterprise.

Summary/Objective

As Senior Engineering Manager, Analytics, you will lead two data and analytics teams, Emburse Analytics and Travel Analytics, that turn travel and expense data into the dashboards, embedded reports, and AI-powered insights our customers use to control spend. Reporting to the Director of Engineering in a hybrid role, you will focus on people and delivery: owning a strong SDLC, partnering with Product on options and tradeoffs, and ensuring good technical decision making.

Essential Functions

Technical

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8+ years of data engineering, analytics engineering, or software development experience, with 3+ years of direct line management, including leading multiple teams

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Enough technical depth in data pipelines, data modeling, and BI to evaluate designs and assess risk and effort, while delegating implementation to senior engineers

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Accountable for the quality and security of customer-facing embedded analytics (Looker and Power BI) and the analytics roadmap, including a governed semantic layer for AI analytics

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Develop, lead, coach, and assess two teams of individual contributors across North America and Europe, growing senior engineers into technical leaders

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Grow a collaborative team culture grounded in trust, open feedback, and accountability

Agile / Process

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Champions agile ways of working and continuously improves team rituals based on what the team learns

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Breaks large initiatives into small, incremental slices that ship value early and often, validated with customers before the next iteration

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Owns the team's SDLC end to end, from refinement and estimation through testing, release, and post-release monitoring

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Partners closely with Product, presenting clear options with tradeoffs in scope, timeline, cost, and risk, and recommending a path forward

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Drives predictable delivery through realistic commitments and visible progress tracking

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Builds secure, compliant practices (SSDLC, GDPR, data residency, access controls) into the regular workflow

Impact

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Leads two analytics teams in delivering accurate, reliable data pipelines, models, and dashboards on budget and on time

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Establishes data quality standards so customers trust the numbers

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Improves engineering quality and efficiency through automation, test coverage, and cost management