This website uses cookies to ensure you get the best experience.

Echo Analytics and our selected partners use cookies and similar technologies (together “cookies”) that are necessary to present this website, and to ensure you get the best experience of it. If you consent to it, we will also use cookies for analytics purposes.

See our Cookie Policy to read more about the cookies we set.

You can withdraw and manage your consent at any time, by clicking “Manage cookies” at the bottom of each website page.

Select which cookies you accept

On this site, we always set cookies that are strictly necessary, meaning they are necessary for the site to function properly.

If you consent to it, we will also set other types of cookies. You can provide or withdraw your consent to the different types of cookies using the toggles below. You can change or withdraw your consent at any time, by clicking the link “Manage Cookies”, which is always available at the bottom of the site.

To learn more about what the different types of cookies do, how your data is used when they are set etc, see our Cookie Policy.

These cookies are necessary to make the site work properly, and are always set when you visit the site.

Vendors Teamtailor

These cookies collect information to help us understand how the site is being used.

Vendors Teamtailor
Echo Analytics career site
Department

Engineering

Connect

With over 30 talented data specialists and software engineers, it is Echo Analytics's biggest team and the heartbeat of our most ambitious projects!


This talented group is essential in delivering our products by building and maintaining large-scale data processing and machine learning pipelines that empower everything we do.

    Team Organization

    To optimize their diverse skills, we’ve structured the team into specialized squads, or “chapters”:

    • Data Engineers and SRE: The team focused on data transformation infrastructure and massive ETL pipelines
    • ML engineers: Engineers who provide powerful algorithms for data modeling and Data Flow designs using machine learning (NLP, image recognition…).
    • Data Analyst: Engineers that analyze vast amounts of data for business insights, whether for our customers or internal needs.
    • Software engineers: Creators of the Echo Platform, our internal tool that shows geospatial data using maps and charts. They specialize in backend and frontend development, working closely with product teams.
    • SDK engineers: Based in Bangalore (following Roam acquisition). Engineers working on mobile programs to track in real-time users’ locations and be able to store and display them.

    Each chapter collaborates to build geospatial datasets and features that empower our five products:

    • Places: A dataset of over 80 million ‘Points of Interest’ (POI) worldwide, offering clean and verified business information.
    • Activity: Insights that provide all attributes to understand customer journeys in and around commercial places - Footfall, catchment area, cross-visitation.
    • Mobility: Working on “Geopersona”, a map-based audience segmentation tool from real-world mobility patterns
    • Echo Internal Platform: Internal platform that blends features from Activity, Mobility, and Places to simplify our operations.
    • Location Solutions: SDK Engineers focused on developing the Roam product for advanced location-based solutions.

    Delivery Process


    Collaboration is our secret sauce and we’ve built up a delivery approach that blends a methodical and energizing mindset:

      • Our teams run on two-week sprints, with Product Managers leading the roadmap. Along the way, standup meetings are a chance to connect, share progress, and ensure everyone is aligned.
      • We gather for the Engineering Demo every two weeks, a bi-weekly meeting where progress is showcased, new features are introduced, and ideas are exchanged.

      • Gemba walks: A ritual where managers engage directly with teams to observe workflows on the field and identify opportunities for improvement.
      • Problem-solving sessions: A daily 30-minute placeholder where any engineering team member can share and tackle challenges together as a team!
      • Tech Obeya: A weekly meeting for managers to discuss burning topics. We centralize all key dashboards (product roadmap, POI Datalake, data delivery performance) to review progress and highlight the areas for improvements

      • Data Analytics weekly wrap-up: Where the Data Analytics team celebrates wins, shares discoveries, and enjoys time together!
      • Back-to-school sessions for Data Analytics: In each session, a team member shares expertise or newly acquired skills, encouraging a continuous learning mindset
      • Data Engineering Chapters: Monthly meetings for data engineers to share ideas, showcase some demo tools, and refine best practices. Think of it as a data engineer’s book club but with way more Python or SQL lines!
      • Machine Learning Wars: Not as dramatic as it sounds (no lightsabers involved). Monthly meetings mainly focused on ML subjects. Everyone is welcome, even non-engineering team members! We share the framework for doing ML at Echo (LLM, Distributed Training, Anti-Patterns…).
      • Hackathons: Two-day creative workshop where Echoers turn ideas into POC solutions inspired by the product roadmap. Last sessions focused on improving efficiency and collaboration between Sales and Data Delivery.
      • Code Reviews and Pair Programming: Regular practices that strengthen engineering expertise, data quality, and team collaboration

    Outstanding metrics

    Numbers of Engineers

    Different Nationalities

    Millions - Number of POIs

    GB - Data Processed Daily

    Billion - Rows Per Day

    Billion - Daily Pings

    Tech Stack

    Design TT2 (2).png

    2025 Challenges & Roadmap

    • Echo Platform

      Developing an internal platform that is the cornerstone of all our products. We have already integrated Mobility (Geopersona) within the platform. Up next? Adding "Places" and "Activity" by year’s end!

    • Delivery on scale

      Using LLM and prompting to transform how we address customer requests. We plan to launch the first version of an AI delivery copilot capable of interpreting customer needs and running precise SQL queries. Following this, we will implement it into the Echo internal Platform.

    • Foundation model

      Enriching our product lines with a Large Geospatial Model (LGM) to support forecasting and simulation. Before training large-scale geolocalization models, we plan to build our foundations on quality datasets and small-scale multi-modal models (POIs, Brands, …).

    Visit our Tech Blog

    Already working at Echo Analytics?

    Let’s recruit together and find your next colleague.