---
title: 'Location Data engineer at amo'
canonical: 'https://feeny.ai/job/location-data-engineer-amo-paris-tcyrf5b3yb7c'
type: 'job'
last_seen: '2026-10-12'
---

# Location Data engineer at amo

- **Company:** amo
- **Location:** Paris, France
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-23
- **Last confirmed live:** 2026-10-12
- **Apply:** https://jobs.ashbyhq.com/amo/6cb7a130-d790-4712-b098-953515c2eb2d

## Job description

We are seeking a highly skilled Location Data Engineer to join our team. In this role, you will work with large-scale datasets generated by our products and turn raw data into meaningful signals, insights, and features. You will work across the entire data lifecycle: building reliable pipelines, exploring and understanding complex datasets, developing features from them, and creating the tools and visualizations needed to understand their quality and impact. This is a technical and product-oriented data role. You'll collaborate closely with product, engineering, and data teams to find what we can learn from our data and turn those learnings into production systems.

As a Data Engineer, your day-to-day will include:

- Making Sense of Data
- Explore large and complex datasets to understand user behavior and identify useful patterns and signals.
- Transform raw data into reliable, well-defined features that can be used by our products and engineering teams.
- Develop a deep understanding of our data: where it comes from, what it represents, its limitations, and how it can be combined to answer new questions.
- Building Data Products
- Design, build, and maintain pipelines that process large volumes of data efficiently and reliably.
- Take ideas from exploration to production: prototype them on historical data, evaluate their quality, and build the pipelines needed to run them at scale.
- Build datasets and features that can power product experiences, internal systems, analytics, and machine learning models.
- Work with technologies such as Spark, DBT, Dagster, BigQuery, ClickHouse, DuckDB, or similar tools depending on the problem at hand.
- Exploring & Analyzing
- Use data to investigate hypotheses, understand behaviors, and answer ambiguous questions.
- Develop metrics and evaluation frameworks to understand whether the signals and features we build actually work.
- Create analyses, dashboards, and visualizations that make complex datasets understandable and help the team make better decisions.
- Build tooling that makes it easier to inspect individual examples, debug data pipelines, and understand why a system produces a particular result.
- From Data to Intelligence
- Work closely with engineers and product teams to identify opportunities where data can make our products smarter.
- Use statistical methods, heuristics, experimentation, or machine learning depending on what is most appropriate for the problem.
- Iterate on features and models based on real-world data and continuously improve their accuracy and reliability.
- Help bridge the gap between exploratory data work and robust systems running in production.
- Continuous Improvement
- Improve the performance, reliability, and maintainability of our data infrastructure.
- Monitor data quality and proactively investigate unexpected changes or anomalies.
- Stay up to date with developments in data engineering, analytics, and machine learning, and bring relevant ideas and technologies into our stack.
- Contribute to a culture of curiosity, craftsmanship, and learning.

## Your Skills & Experience

- Strong software engineering fundamentals and experience working with data-intensive systems.
- Very comfortable with SQL and manipulating large datasets.
- Experience with one or more modern data technologies such as Spark, DBT, Dagster, BigQuery, ClickHouse, DuckDB, or equivalent tools.
- Strong analytical skills: you enjoy digging into data, testing hypotheses, and understanding why something behaves the way it does.
- Ability to turn exploratory analysis into reliable, production-ready data pipelines and features.
- Familiarity with data modeling, pipeline orchestration, and large-scale data processing.
- Ability to communicate findings clearly through metrics, visualizations, dashboards, or other tools.

## Preferred Qualifications

- Experience building data products or features directly used by consumer-facing products.
- Experience working with high-volume event, behavioral, sensor, geospatial, or time-series data.
- Familiarity with statistics, machine learning, or feature engineering.
- Experience taking a data problem from an ambiguous question through exploration, prototyping, evaluation, and production.
- Experience building internal tools or visualizations for exploring and debugging complex datasets.

Life at amo To ensure that everyone is set up for success within our way of working, we work together onsite 5 days a week. We wanted to make sure coming to the office was as comfortable as possible for you: We chose a location in central Paris, near Opéra (Metro lines 3, 8, 9 and RER A). We have a beautiful Parisian-style office with high ceilings, balconies, and huge windows. So a lot of natural light!

Because life outside of work should also be stress-free, we cover:

- Health care (100% coverage).
- Maternity Leave, Paternity Leave, Second Parent Leave (salary maintained at 100%).
- Vacation days: 8–9 weeks (total) per year:
- 5 weeks of paid time off;
- 1–2 additional weeks (RTT, based on our company contract);
- ~11 bank holidays.

We shut down entirely twice a year, two weeks in summer and one week in winter, to allow everyone to truly recharge and avoid prolonged slowdowns. These pauses are part of your total vacation time, giving everyone a real chance to unplug and recharge. No Slack, no email, no FOMO.

We love the diverse perspectives we get from having people from all over the world join us (68% of our team is international), and so we of course support relocation to Paris with:

- Help and sponsored visa process.
- 1 month of Airbnb 100% covered by amo upon arrival.
- Assistance from a trusted relocation agency to find your permanent home.
- Help with French paperwork like opening a French social security account, tax forms, getting your carte vitale (free healthcare), and more.
- French lessons to be fully set with your new Parisian life.

## About amo

## Company Overview

- **One-liner**: amo is building a collection of social apps (ID, Bump, Sugar) designed to bring friends closer together in a digital space, moving away from scrolling strangers to sharing moments with real friends.
- **Entity Type**: Private (funding stage not publicly disclosed)
- **Headquarters**: Paris, France
- **Founded**: Not publicly available
- **Founders**: Not publicly available

## Core Business

- Primary industry/industries: Consumer social media / mobile applications
- Target customers: B2C – individuals and their friend groups, especially those who want a more private, friend-focused online experience
- Mission or purpose statement: “We believe that friendship still deserves a place online.” (from amo.co)

## Products & Services

- **ID**: A collaborative social profile board where you and your friends can express yourselves together.
- **Bump**: A map app “for friends” that gives you a new home on your phone for the people and places most important to you.
- **Sugar**: A chat app that goes beyond the traditional messaging bubble, offering an unlimited canvas to turn conversations into art.

All three apps share a single profile, friendships, and settings across the amo ecosystem, allowing users to pick and choose what they use.

## Market Standing

- **Valuation / Latest Funding**: Not publicly disclosed. The company states it is “backed by some of the best tier-1 investors in the world” and is “growing at a pace that hasn’t been seen in our space in the past five years.”
- **Key Metric**: 148 total employees (per Built In profile as of mid-2026)
- **Notable Investors/Partners**: Not named in available sources, but described as “tier-1 investors.”
- **Growth Signals**: 17 nationalities represented; over half the team is international; one in four employees relocated cities or countries to join; multiple senior engineering roles open across Android, iOS, backend (Rust, Safety, AI), SRE, and product design.

## Competitive Advantages

- **Multi-app ecosystem with a shared identity**: Unlike single-app social platforms, amo’s suite lets users carry their profile and friends across apps without redundancy.
- **Friend-first focus**: The company deliberately avoids the “scrolling strangers” model and builds features that mirror real-life friend interactions (maps, collaborative boards, creative chat).
- **Velocity and experimentation**: The culture values speed, quick iteration, and learning from mistakes; new apps are released independently rather than crammed into one tab bar.
- **Global talent strategy**: An intentionally international team with relocation support and English as the working language, enabling access to top talent worldwide.

## Strategic Focus

- **Expand the app ecosystem**: Continue launching new, standalone apps that serve specific friend-group needs.
- **Balance art and science**: Blend creative, fun product design (“making people smile”) with rigorous engineering and data-driven decisions.
- **Scale the team**: Active hiring across engineering, AI, SRE, product design, and recruiting – with an emphasis on in-office collaboration in Paris.
- **Maintain a lean, performance-driven culture**: Emphasize outcomes over busywork, fast decision-making, and a “healthy intensity.”

## Why Work Here

- Culture highlights: “Velocity over all else,” high ownership, conviction over consensus, fast iteration. The company describes itself as a “performance machine” where ambitious goals are set and celebrated. The team is described as “a group of friends who have spent our lives building stuff for friends.”
- Remote/hybrid/office policy: In-office at the Paris headquarters. Relocation support is provided, and one in four employees has moved to join.
- Notable perks or engineering culture: Structured, bias-mitigating interviews with a fast decision cycle (average 72 hours). Technical depth is valued – interviews include debugging real code, concurrency/design, and cultural panels that include a team lunch. The engineering stack involves Rust, AI, Android, iOS, and SRE roles.
- Diversity: 17 nationalities, English as the working language (no English required at hire, but learned within months), and a global hiring philosophy.

## Sources

1. [amo.co](https://amo.co/)
2. [amo Careers Page](https://amo.co/jobs/)
3. [Built In Company Profile](https://builtin.com/company/amo)
4. [amo Interview Process](https://amo.co/interview-at-amo/)
5. [Welcome to the Jungle Jobs](https://www.welcometothejungle.com/en/companies/amo/jobs)

## Other roles at amo

- [Portugal Content Specialist](https://feeny.ai/job/portugal-content-specialist-amo-paris-fq128ytce0nh) — Paris, France
- [France Content Specialist](https://feeny.ai/job/france-content-specialist-amo-paris-emv9qs66x3wp) — Paris, France
- [User Acquisition - Events](https://feeny.ai/job/user-acquisition-events-amo-paris-t91sfd5vsy2f) — Paris, France
- [Brazil Content Specialist](https://feeny.ai/job/brazil-content-specialist-amo-paris-w71znsz7zsgx) — Paris, France
- [Indonesian Content Specialist](https://feeny.ai/job/indonesian-content-specialist-amo-paris-tj5wv4p1tkqp) — Paris, France
- [Senior Search Engineer](https://feeny.ai/job/senior-search-engineer-amo-paris-jw2b5qd4n3ed) — Paris, France
- [Data Engineer, Places](https://feeny.ai/job/data-engineer-places-amo-paris-dks384s1y085) — Paris, France
- [Senior Data Engineer](https://feeny.ai/job/senior-data-engineer-amo-paris-1n6bwrhkeb8d) — Paris, France
- [Japan Content Specialist](https://feeny.ai/job/japan-content-specialist-amo-paris-3raftzj15jxw) — Paris, France
- [Australia Content Specialist](https://feeny.ai/job/australia-content-specialist-amo-paris-rx5t328yw9eh) — Paris, France