---
title: 'Analytics Engineer at Uberall'
canonical: 'https://feeny.ai/job/analytics-engineer-uberall-south-africa-eq2qgce91yv0'
type: 'job'
last_seen: '2026-10-28'
---

# Analytics Engineer at Uberall

- **Company:** Uberall
- **Location:** South Africa
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-10-21
- **Last confirmed live:** 2026-10-28
- **Apply:** https://jobs.ashbyhq.com/uberall/34dc8010-003c-4306-82f8-d7c21659b44d

## Job description

About the role: The Analytics Engineer turns raw product, commercial, and vendor data into trusted data products that teams across Uberall use to make decisions. This role owns the transformation layer of our Databricks lakehouse, from curated models through to the datasets and dashboards stakeholders use every day, and keeps it reliable, documented, and fast. The work is analytical and creative in equal measure: data products include visual assets, so strong modeling needs to come with a clear sense of how people will actually read and use the data.

What you will own: The curated data layer

- Design and build dbt models that turn raw sources into trusted curated data
- Apply dimensional modeling to shape facts and dimensions for analytics
- Model transactional sources that originate from CDC and third normal form patterns
- Define and enforce naming conventions and project structure

The data consumption layer

- Build and maintain data products and datasets for internal stakeholders
- Deliver clear, well-designed reporting in Metabase and Pigment
- Translate business questions into data models with stakeholders
- Enable safe, governed data sharing across teams

Data in production

- Own the health of production pipelines orchestrated in Databricks or Apache Airflow
- Set up monitoring, alerting, and data quality checks that catch issues early
- Manage CI/CD pipelines, schema migrations, and safe releases
- Tune performance and cost of workloads on columnar engines

Development patterns, documentation, and governance

- Establish reusable development patterns and code review standards
- Maintain model documentation, lineage, and column-level metadata
- Contribute to governance standards and data contracts with stakeholders and source teams
- Support vendor and third-party data ingestion as a secondary focus

What you bring:

Data modeling and transformation

- Proven experience with dimensional modeling for analytics warehouses
- Hands-on production experience with dbt
- Understanding of CDC and third normal form modeling for MySQL or PostgreSQL sources
- Experience with lakehouse architecture and Delta Lake

Engineering practice

- Strong SQL and confident, practical Python
- Comfort with Git, the Linux shell, and code review workflows
- Experience structuring and orchestrating workflows in Databricks or Apache Airflow
- Production experience with CI/CD, migrations, monitoring, and alerting

Platform and performance

- Experience with AWS and Databricks
- Demonstrated ability to model for and performance-tune columnar engines
- Experience loading data from vendors and third-party sources
- Experience with data quality processes; familiarity with data contracts and semantic layers is a plus.

Working with stakeholders

- Visualization experience with Metabase, Pigment, or similar tools
- Ability to explain technical trade-offs clearly to non-technical colleagues
- Plans and delivers complex work independently, with minimal supervision
- Raises issues early and comes with proposed solutions

What success looks like

- Stakeholders trust the curated data and use it without reconciling numbers themselves
- Production pipelines run reliably, and issues surface through alerts rather than stakeholder reports
- New data products ship through a consistent, tested, and documented pattern
- Models are documented well enough that others can use and extend them confidently
- Workloads stay fast and cost-efficient as data volumes grow
- Reporting moves off ad-hoc queries and onto the governed data layer
- Improvements to the data platform are proposed and driven proactively, not only delivered on request

## Why this role matters

- Decisions across Uberall depend on consistent, trustworthy data, and this role is where that consistency is built
- A strong transformation layer lets the business scale reporting without scaling manual effort
- The patterns set here become the foundation the rest of the data team builds on

AI and innovation expectations

- Use AI coding assistants to write, test, refactor, and document SQL, dbt, and Python, with human review built into the quality process
- Explore AI to automate documentation, data quality checks, and self-serve analytics, so stakeholders get answers faster

## About Uberall

## Company Overview
- **One-liner**: Uberall provides an AI-powered multi-location marketing platform that helps brands manage their digital presence across search, social, maps, and AI discovery to drive local visibility, engagement, and revenue.
- **Entity Type**: Private (Growth Stage, €143M total funding)
- **Headquarters**: Berlin, Germany
- **Founded**: 2013
- **Founders**: David Federhen and Florian Hübner

## Core Business
- Primary industry: Software Development / Multi-Location Marketing Technology (MarTech)
- Target customers: B2B, serving multi-location brands (retail, hospitality, food & beverage, automotive) and global enterprises
- Mission or purpose statement: "Empowering Brands to Thrive Locally" — connecting online discovery with real-world experiences so local businesses and global brands can succeed everywhere customers search, shop, and connect.

## Products & Services
- **Listings Management**: Create, publish, and optimize business listings across 150+ directories (Google, Apple, voice search, AI-powered tools) to boost visibility and foot traffic.
- **Review Management**: Monitor, respond to, and improve reviews across all locations using AI for bulk replies, sentiment analysis, and reputation management.
- **GEO Studio**: A Generative Engine Optimization solution that helps brands provide the accuracy, trust signals, and local context AI needs to select their locations.
- **Locator & Local Pages**: SEO and GEO-optimized local pages with fast-loading, mobile-optimized experiences and built-in CTAs for directions, booking, and reviews.
- **Local Social**: AI-powered social media posting across Facebook, Instagram, LinkedIn, Google, and Apple to drive engagement and conversions.
- **Location Performance Optimization (LPO)**: AI-powered insights tracking search visibility, conversions, sentiment, competitor trends, and revenue impact.
- **UB-I (Agentic AI)**: An always-on AI agent that continuously monitors locations, identifies priorities, and orchestrates actions to boost visibility, engagement, and revenue.
- **Analytics**: Track and maximize local marketing performance with data-backed insights and growth opportunities.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (Private company)
- **Key Metric**: €143M total funding raised to date (as of company website); estimated annual revenue of $25.0M (per LinkedIn data)
- **Notable Investors/Partners**: Trusted by brands including KFC, Søstrene Grene, QPark, and Barceló. G2 Fall 2025 award winner for Best Support, Momentum Leader, Easiest Admin, and Easiest To Do Business With.
- **Growth Signals**: Manages over 1.3 million locations across 194 countries; 315 employees (+1.7% YoY growth); 9 prior funding rounds with $175.6M in total funding (per LinkedIn); expanding globally with offices in Germany, US, Philippines, Canada, and France.

## Competitive Advantages
- **First-mover in GEO (Generative Engine Optimization)**: Offers a dedicated solution (GEO Studio) to optimize for AI-driven search discovery, a rapidly growing market.
- **Comprehensive, All-in-One Platform**: Combines listings, reviews, social, local pages, analytics, and AI agents in a single platform — reducing the need for multiple vendors.
- **Agentic AI (UB-I)**: Differentiated by an always-on AI agent that proactively monitors and optimizes location performance, going beyond passive analytics.
- **Global Scale & Local Depth**: Manages over 1.3M locations in 194 countries, with deep local market expertise across retail, hospitality, F&B, and automotive.
- **Strong Brand Trust**: Recognized by G2 as a leader and trusted by major global brands.

## Strategic Focus
- **AI-First Innovation**: Deep investment in Generative Engine Optimization and Agentic AI (UB-I) to stay ahead of the shift toward AI-powered local discovery.
- **Global Expansion**: Continuing to grow presence across North America, Europe, and Asia-Pacific, with a distributed workforce spanning 30+ countries.
- **Platform Consolidation**: Positioning as the single platform for multi-location brands to manage all aspects of local digital presence, from listings to AI-driven optimization.
- **Customer Obsession**: Focus on delivering measurable ROI for clients through data-driven insights and automated actions.

## Why Work Here
- **Culture & Values**: Described as "truly human culture" with high performance, openness, collaboration, and authenticity. Values include "Be Customer Obsessed," "Be Bold & Drive Change," "Demonstrate Passion & Performance," and "Grow Together." Inclusion is a core operating principle, not just a program.
- **Remote/Hybrid Policy**: "Choice-First environment" — employees can work from global offices or remotely; coming to an office is not required. Offices available for collaboration.
- **Global & Diverse Team**: Over 400 Uberallers representing 50+ nationalities across 30+ countries.
- **Growth & Development**: Learning Grant program, Power Skills Academy, and Leadership Foundations for continuous development.
- **Compensation**: Competitive benefits tailored to local markets; Long-term incentive plans through Virtual Stock Option Plan (VSOP) and Equity Plan (ESOP) for all eligible employees.
- **Engineering Culture**: AI-first organization with a human approach to hiring. Encourages AI fluency and curiosity; values using AI to support, not replace, human work.
- **Hiring Process**: Transparent, respectful process with initial chat, team interviews, culture & values interview, and structured onboarding. Human-driven decision-making at every stage.

## Sources
1. [uberall.com - Careers Page](https://uberall.com/en-us/company/careers)
2. [uberall.com - About Us](https://uberall.com/en-us/company/about-us)
3. [uberall.com - Homepage](https://uberall.com/en-us)
4. [linkedin.com - Uberall Company Page](https://www.linkedin.com/company/get-uberall)
5. [cbinsights.com - Uberall Profile](https://www.cbinsights.com/company/uberallcom)

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