Overview

Location

Remote

Team

Engineering

Compensation

244K

287K

/ yr

Experience level

Mid-level

Occupation

Full-time

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Posted 30 mins ago

Senior Manager, Analytics Engineering at Base

Location

Remote

Experience level

Mid-level

Team

Engineering

Occupation

Full-time

Compensation

244K

287K

/ yr

Role Overview

Lead the Analytics Engineering team at Base to deliver high-impact, trustworthy data infrastructure and analytics tools that support finance, HR, CX, compliance, and product teams. You'll architect scalable data models, promote data quality, and integrate LLM- and AI-driven analytics across the organization.

Key Responsibilities

Team Leadership: Hire, mentor, and grow a team of analytics engineers. Provide technical and strategic guidance.
Data Architecture: Design and implement scalable, reliable core data models and marts.
Data Quality & Governance: Establish rigorous testing, validation, and monitoring frameworks.
Domain Expertise: Develop deep understanding of stakeholder data (finance, HR, CX, compliance) to solve business-specific problems.
AI & LLM Integration: Build data foundations optimized for generative AI and large language model use cases.
Tooling & Delivery: Oversee dashboards, ad-hoc reports, and self-service tools that enable data-driven product decisions.
Business Impact: Translate analytics into actionable insights that directly support company goals.

Required Skills & Experience

Proven experience leading data/analytics teams, including hiring and mentorship
Deep expertise in data modeling, ETL/ELT, and tools like DBT, Airflow, Snowflake, Hex
Strong software engineering practices (Git, CI/CD, OOP, version control)
Strong SQL skills; experience building scalable analytics workflows
Demonstrated ability to collaborate across technical and business teams (e.g., product, legal, data science)
Solid foundation in statistics and probability
Experience with CX and Compliance analytics
Passion for AI and LLMs with ideas for future-forward analytics systems

Nice to Have

Experience developing AI-optimized data marts or working with prompt engineering
History of bridging gaps between technical teams and business stakeholders
Ability to scale internal tooling and data applications for diverse teams

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