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Data Full Stack (Senior/Staff) - 65k~110k € image - Rise Careers
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Data Full Stack (Senior/Staff) - 65k~110k €

🇫🇷 La langue de travail à Didask est l'anglais et sa maîtrise est requise pour nous rejoindre. Néanmoins, nous publions l'intégralité de nos offres d'emploi en français et en anglais. Vous pouvez retrouver toutes nos offres d'emploi sur cette page, ainsi que plus d'informations sur Didask, notre culture et nos avantages.

🇬🇧🇺🇸 While English is our working language at Didask and proficiency is required to join us, we publish all our job openings in both English and French. You can find all our positions on this page, along with more information about Didask, our culture and benefits.

About Didask

Didask is a SaaS eLearning platform that combines cognitive science research with advanced AI to create highly effective training programs. Our pedagogical assistant—unique in the market—guides organizations in designing adaptive learning experiences with proven educational impact.

Founded by researchers from École Normale Supérieure in Paris and backed by European investment since 2021, we're building AI tools specifically designed for learning, not generic content generation. Our mission is to transform education by making scientifically-grounded, impactful learning accessible to all organizations.

Our core values

Each team member brings something unique, but we are united by shared values that guide us every day:

  • Distributed ownership: Responsibility is shared across the team. Everyone, from junior to senior, takes ownership of their projects and makes decisions autonomously with the trust and support of the team.

  • A written-first culture: We favor written communication, ensuring transparency and accessibility for everyone. This approach has allowed us to reduce meetings and improve the clarity of our collaboration.

  • Impact-driven work: Our goal is simple—contribute meaningfully to Didask's success. We work in an agile way to stay flexible, focused, and ready to adapt.

  • Cross-functionality and feedback: Open communication and collaboration are at the heart of everything we do. Everyone, regardless of their role, is encouraged to share ideas, express opinions, and give or receive constructive feedback.

About the Data Team

The Data Team at Didask builds analytics infrastructure that powers company-wide decision making and collaborates with Engineering to develop AI-powered educational tools.

We embrace a full-stack mindset where each team member owns their entire data product (internal or external) and is capable of managing every part of the data chain from ingestion and modeling to interfacing directly with clients to ensure their needs are met.

We believe data practitioners are software engineers and should apply the same best practices to ensure high output quality, such as modular design, separation of concerns, robust testing and collaborative development processes.

Since launching in early 2024, our data team has evolved into a core pillar of the organization. We are now expanding our team to meet growing demands from both internal stakeholders and product.

As the second person recruited to this team, you'll join us at this exciting inflection point and play a crucial role in our continued growth and development!

Our current tech stack includes:

  • Ingestion: Airbyte, Fivetran, and custom Python jobs

  • Transformation: DBT

  • Storage and Compute: Snowflake (data warehouse and data lake)

  • Dashboarding: Metabase

  • Reverse ETL: Python and Lambda functions

What you'll do

  • Deliver value to internal stakeholders: understand their business processes deeply and own solutions across the entire data chain - from ingestion and data modeling to dashboards and data products

  • Own critical parts of our data infrastructure, from decision-making to full deployment. A current priority is selecting and implementing our data orchestration tool and improving the monitoring of our data jobs.

  • Design and build our product analytics pipeline from the ground up, enabling our product team to gain deep insights into client usage patterns and behaviors

  • Make our AI-powered product more robust: shape and build our evaluation pipelines and testing frameworks, to help our product and prompt engineering teams iterate faster and more confidently.

  • Build foundations for data team excellence: define strong shared guidelines and best practices, and create simple, robust internal products that maximize reusability and minimize maintenance.

  • Contribute to team growth: help shape our culture, improve our attractiveness to candidates, and enhance our hiring process to bring in top-level autonomous full stack data practitioners aligned with our values and mission.

Why join us now ?

  • Be part of a team transforming education - we're not building yet another learning management system, but revolutionizing how people learn by combining cognitive science, learning design, and cutting-edge generative AI to create truly effective educational experiences.

  • Gain a deep understanding of how a scale-up functions - your work will require mastering business processes across departments to implement meaningful data solutions. From product, to customer success, to finance: you'll be in a unique position to understand the inner workings of the company.

  • Own your work with autonomy and responsibility: This position requires initiative and self-drive. We don't want to tell you what to do—we want you to tell us what needs to be done, while collaborating toward our shared team and company missions.

  • Shape the future of our data team - as we expand from a solo team member to 3-4 data professionals by the end of 2025, you'll have the unique opportunity to help build our data foundation, influence our strategy, and grow into leadership as we strengthen and scale our data capabilities.

About You

You might be a good fit if most of this sounds like you:

  • You have 4+ years of experience in a data practitioner role: You have a track record of proactively identifying and addressing stakeholder needs by designing and implementing impactful data solutions.

  • You are "T-shaped" with a generalist mindset: You are eager to be a full stack data practitioner, and owning solutions end-to-end. While experience across the entire data value chain or our specific tech stack is ideal, it isn't mandatory and we value deep expertise in one specific area (data engineering, analytics, machine learning), as long as you are excited about developing your skills outside of your comfort zone.

  • You have strong Software Engineering skills: You write high quality code, and adhere to software engineering best practices and standards. Specific expertise in python is valued although not mandatory.

  • You have strong written communication skills: You excel at clearly articulating project goals, aligning stakeholders, and summarizing needs both succinctly and comprehensively. You proactively keep team members informed about project status and ensure documentation remains clear and accessible.

  • Impact is your priority: You proactively engage with stakeholders to understand their true needs, even when not explicitly stated. You focus on delivering solutions that create measurable value rather than just fulfilling requirements.

  • You are pragmatic...: You break down complex problems into manageable pieces and prioritize making steady progress over pursuing perfect but delayed solutions. You're comfortable with iterative approaches that deliver value quickly.

  • ...While pushing for excellence: You balance short-term pragmatism with long-term quality by thoughtfully addressing technical debt. You understand when to move quickly and when to invest in robustness, maintaining that crucial equilibrium.

  • You strive for simplicity: You transform complex processes into elegant, straightforward solutions. You recognize that the most maintainable and scalable systems are often the simplest ones.

  • You are excited about reshaping education: You're motivated by our mission to transform how people teach and learn through innovative data solutions and AI-powered educational tools.

Important notes:

  • We hire people, not roles: While we value experience, we're primarily looking for individuals with high potential, curiosity, and a strong fit with our team. Show us why you'd thrive in our environment and culture.

  • We value diverse backgrounds: We don't filter candidates simply based on academic credentials or previous employers. Your past doesn't define who you are today. Instead of trying to fit a predetermined mold, show us what makes you unique and how your distinctive perspective would enhance our team.

Interview Process

  • Written questions (application form)

  • Introductory call (30min visio, w/ Data Lead)

  • Technical assessment (take-home assignment + 1h visio to debrief w/ Data Lead and software engineer)

  • Presentation of previous project (1h visio or on-site, w/ Data Lead and business stakeholder)

  • Culture fit interview with a co-founder (30min)

🇫🇷 Retrouvez les avantages réservés aux salariés de Didask sur cette page.

🇬🇧🇺🇸 You'll find our benefits and perks on this page.

🇫🇷 Sauf mention contraire, toutes nos offres sont accessibles en télétravail complet à condition de travailler dans un fuseau horaire proche de celui de Paris et de disposer des bonnes conditions de travail (notamment connexion Internet). Attention, nous ne pouvons à l'heure actuelle embaucher que des résidents fiscaux français.

🇬🇧🇺🇸 Unless specified otherwise, all positions are fully remote, provided you work in a timezone close to Paris and have suitable working conditions (including Internet connection). Please note that we can currently only hire French tax residents.

Average salary estimate

$87500 / YEARLY (est.)
min
max
$65000K
$110000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Data Full Stack (Senior/Staff) - 65k~110k €, Didask

Didask is searching for a talented Data Full Stack (Senior/Staff) to join our dynamic team in Bagnolet, where we're revolutionizing education through our innovative SaaS eLearning platform. Our platform blends cognitive science research with advanced AI to create impactful training programs. As a Data Full Stack practitioner, you'll be diving into a variety of projects that challenge your expertise across the entire data chain—from ingestion to dashboarding. You will play a pivotal role in ensuring that our analytics infrastructure meets the demands of our stakeholders while utilizing our current tech stack, including Airbyte, DBT, and Snowflake. You'll also contribute to shaping our data team's culture and practices, ensuring we maintain high standards and our values of ownership, transparency, and collaboration. This is an exciting opportunity to be one of the foundational members of a growing data team, where your input will directly influence our direction and success. If you're passionate about using data to transform how people learn and you're eager to tackle complex challenges, we want you at Didask. Join us on our mission and make a real difference in education!

Frequently Asked Questions (FAQs) for Data Full Stack (Senior/Staff) - 65k~110k € Role at Didask
What are the key responsibilities for a Data Full Stack at Didask?

As a Data Full Stack at Didask, you will own solutions across the entire data chain—from data ingestion to visualization. You'll engage deeply with stakeholders to understand their needs, develop our analytics pipeline, and enhance our AI educational products. Additionally, you'll contribute to defining best practices and guidelines for our data infrastructure, ensuring robust and maintainable solutions.

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What skills are required to succeed as a Data Full Stack at Didask?

To succeed as a Data Full Stack at Didask, candidates should have at least 4 years of experience in data roles, strong software engineering skills, and the ability to communicate effectively. Familiarity with tools like Airbyte, DBT, Snowflake, and Python is beneficial, although we also value strong expertise in one area of data practices. Most importantly, a proactive approach to driving impact and a passion for reshaping education through data is essential.

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What is the team culture like for the Data Full Stack position at Didask?

The culture at Didask is centered around distributed ownership and a written-first communication style. We prioritize collaborative feedback and open communication, promoting an agile work environment where team members take initiative to solve problems. As a Data Full Stack practitioner, you will contribute to enhancing our team culture and nurturing the values we uphold.

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Is remote work an option for the Data Full Stack position at Didask?

Yes, all positions at Didask, including the Data Full Stack role, are fully remote as long as you work within a timezone close to Paris. We value flexibility, ensuring that our team members have suitable working conditions. However, please note that we can currently only hire candidates who are tax residents of France.

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What growth opportunities are available for a Data Full Stack at Didask?

Joining Didask as a Data Full Stack offers significant growth opportunities. You will have the chance to shape the data team's direction, influence strategies, and expand into leadership roles as the team grows. This role also allows you to deepen your understanding of cross-functional business processes, resulting in impactful data solutions that transform education.

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Common Interview Questions for Data Full Stack (Senior/Staff) - 65k~110k €
Can you describe your experience with data ingestion tools?

When answering this question, highlight any specific ingestion tools you have used, such as Airbyte or Fivetran. Discuss your approach to integrating data from various sources and ensuring data quality during the ingestion process, showcasing your technical skills and problem-solving capabilities.

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How do you ensure the quality of your code as a Data Full Stack practitioner?

Discuss your commitment to following software engineering best practices, such as writing tests, conducting code reviews, and maintaining clear documentation. Explain how you approach technical debt and ensure your codebase remains clean and manageable over time.

Join Rise to see the full answer
How do you prioritize stakeholder needs when developing data solutions?

Emphasize your proactive engagement with stakeholders to deeply understand their requirements. Provide examples of how you've gathered feedback to iterate on solutions effectively, ensuring their projects derive maximum value from your data products.

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What methods do you use to visualize data for stakeholders?

Highlight your experience with visualization tools such as Metabase. Explain how you customize dashboards to meet user needs and present data in a meaningful way, using storytelling techniques to guide stakeholders in their decision-making processes.

Join Rise to see the full answer
Can you share an example of a challenging data problem you've solved?

Reflect on a specific challenge you've faced, detailing the problem, your approach, and the outcome. Emphasize your analytical skills and how you collaborated with others to achieve a solution, demonstrating your effectiveness as a Data Full Stack team member.

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Describe your experience with data modeling.

Discuss any specific methodologies or frameworks you’ve employed in data modeling, how you ensure accuracy and efficiency, and how these models have influenced business decisions or product developments in your previous roles.

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How do you stay updated with the latest trends in data technology?

Talk about the resources you utilize, such as attending conferences, participating in online forums, or taking courses, highlighting your commitment to continuous learning and applying new techniques to your work.

Join Rise to see the full answer
What strategies do you implement for effective cross-functional collaboration?

Exemplify your approach to working with other teams, such as product and engineering, to ensure everyone is aligned. Discuss how you use communication tools and frameworks to facilitate collaboration and gather insights from diverse perspectives.

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How do you handle high-pressure situations or tight deadlines in data projects?

Illustrate your time management strategies, such as breaking down projects into manageable tasks and maintaining open lines of communication with your team. Highlight how you prioritize effectively to meet deadlines while ensuring quality in your work.

Join Rise to see the full answer
What excites you about working at Didask as a Data Full Stack?

Articulate your passion for education and data-driven solutions. Share specific aspects of Didask’s mission and culture that resonate with you, demonstrating your commitment to contributing meaningfully to the team’s goals.

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Didask est une jeune société qui repense depuis 2014 la formation et l'éducation avec les apports du numérique. L'équipe DIDASK accompagne et outille les établissements d'enseignement supérieur, les... organismes de formation et les entreprises da...

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DATE POSTED
March 13, 2025

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