Technology, Information and Internet

Gemma Analytics

11-50

Germany

We are Gemma Analytics: a Berlin-based company specializing in generating insights in high-performance data infrastructure. Gemma was founded in early 2020 by two data enthusiasts. Ever since, we have helped over 70 companies to become more data-driven and successful. We have a fun, honest, and inclusive work environment. We are always looking for data-minded people we can learn from.

## Tasks

Gemma Analytics is data-driven and helps clients to become more data-driven. 

As our Senior Data & Analytics Engineers, you play a critical role in helping our clients unlock business value from their data. You’re not just technically strong — you’re a Data Magician who uncovers structure in chaos and turns raw data into meaningful, actionable insight. You dig into complex datasets, spot what others overlook, and guide clients toward pragmatic, high-impact solutions.

But your impact doesn’t stop at client work. As a senior team member, you act as a sparring partner and coach to your colleagues. You’re someone others turn to for advice on technical challenges, project structure, and best practices — and you’re excited to help them grow. 

You have the opportunity to work on difficult problems while helping startups and SMEs to make well-informed decisions based on data.Challenges: 

* As we are tooling-agnostic, you will touch on multiple technologies and understand the in’s & out’s of what is currently possible in the data landscape
* Collaborate with domain experts and client stakeholders to solve data challenges across a variety of industries
* Support and mentor other team members through code reviews, pair programming, and knowledge sharing
* Lead internal sparring sessions and contribute to developing team-wide best practices and scalable project structures 

**Technologies you’ll use**

Working with multiple clients, we are in touch with many technologies, which is truly exciting. We use state-of-the-art technologies while being fully pragmatic (we do not crack a walnut with a sledgehammer). We follow an ELT philosophy and divide the tasks between Data Engineering and Analytics Engineering accordingly.

The following technologies constitute our preferred data tech stack:

Data Loading

* For our clients, we either use a scheduler (e.g. Apache Airflow or Prefect) and run Python DAGs with it - we also like to work with dlt as a framework
* For standard connectors, we work with Fivetran or Airbyte Cloud preferably

Data Warehousing

* For smaller data loads, we mostly use PostgreSQL databases
* For larger datasets, we mostly work with Snowflake or BigQuery

Data Transformation

* We love to use dbt (data build tool) since 2018 - we can also work without it, yet we are fans to be honest
* It is important to us that we work version-controlled, peer-reviewed, with data testing, and other engineering best practices

Data Visualization

* For smaller businesses with < 100 FTE, we mostly recommend Metabase or Superset as a powerful open-source reporting tool
* For specified needs and a centralized BI, we recommend PowerBI or Tableau
* For a decentralized, self-service BI with more than 50 users, we recommend Looker, Holistics, or ThoughtSpot
* We are always on the lookout for new tools, at the moment we are excited about Lightdash, Omni, dlt, and other tools

## Requirements

We believe in a good mixture of experience and upside in our team. We are looking for both types of people equally - for this role, we require more expertise and proof of trajectory.

Besides that, **we are looking for the following**:

* 3–4 years of hands-on experience in data engineering or analytics engineering, with a strong focus on building and maintaining robust data pipelines and analytics-ready data models
* Proficient in SQL and experienced with relational databases, capable of translating complex business logic into clear, maintainable queries
* Hands-on experience using dbt (preferably dbt Cloud) in production environments, following best practices for modular, testable, and documented code
* Solid understanding of data modeling techniques (e.g., Kimball dimensional modeling, Data Vault, star/snowflake schema) and data warehousing principles
* Experience working with modern data stack tools, such as Snowflake, BigQuery, Airflow, Airbyte/Fivetran, Git, and CI/CD workflows
* Proficient in Python (or a similar scripting language) for use cases such as API integration, data loading, and automation
* Strong communication skills in English (written and spoken), with the ability to explain technical decisions and collaborate with both technical and non-technical stakeholders
* Comfortable working in client-facing projects, navigating ambiguity, and delivering high-quality results with minimal oversight
* Experience coaching or mentoring junior team members through code reviews, sparring, and knowledge sharing
* Bonus: Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker) to support end-to-end workflows or assist analysts
* Bonus: Fluency in German

## Benefits

We are located in Berlin, close to Nordbahnhof. We are currently 20 colleagues and will grow to 22 colleagues this year. Other perks include:

* We are a hybrid company that meets in the office twice a week - one common office day and one flexible day
* We allow for intra-EU workcations for up to 3 months a year (extra-EU workcations also if this is allowed)
* We have an honest, inclusive work environment and want to nurture this environment
* We don’t compromise on equipment - a powerful Laptop, extra screens, and all the tools you need to be effective
* We will surround you with great people who love to solve (mostly data) riddles
* We believe in efficient working hours rather than long working hours - we focus on the output rather than the input
* We learn and share during meetups, lunch & learn sessions and are open to further initiatives
* We pay a market-friendly salary and we additionally distribute at least 20% of profits to our employees
* We are fast-growing and have technology at our core, yet we do not rely on a VC and operate profitably
* We have a great yearly offsite event that brings us all together for a full week, enjoying good food, and having a good time (2021: Austria, 2022: Czech Republic, 2023+2024: Germany, 2025: Spain)

**How you’ll get here**

1. CV Screening
2. Phone/Coffee/Tea Initial Conversation
3. Hiring Test @home
4. Interviews with 2-3 future colleagues
5. Reference calls
6. Offer + Hired

Looking forward to your application :)

Employee

Professional / Experienced

We are Gemma Analytics: a Berlin-based company specializing in generating insights in high-performance data infrastructure. Gemma was founded in early 2020 by two data enthusiasts. Ever since, we have helped over 70 companies to become more data-driven and successful. We have a fun, honest, and inclusive work environment. We are always looking for data-minded people we can learn from.
<h2 id="tasks">Tasks</h2>
Gemma Analytics is data-driven and helps clients to become more data-driven. 
As our Senior Data &amp; Analytics Engineers, you play a critical role in helping our clients unlock business value from their data. You’re not just technically strong — you’re a Data Magician who uncovers structure in chaos and turns raw data into meaningful, actionable insight. You dig into complex datasets, spot what others overlook, and guide clients toward pragmatic, high-impact solutions.
But your impact doesn’t stop at client work. As a senior team member, you act as a sparring partner and coach to your colleagues. You’re someone others turn to for advice on technical challenges, project structure, and best practices — and you’re excited to help them grow. 
You have the opportunity to work on difficult problems while helping startups and SMEs to make well-informed decisions based on data.Challenges: 
<ul>
<li>As we are tooling-agnostic, you will touch on multiple technologies and understand the in’s &amp; out’s of what is currently possible in the data landscape</li>
<li>Collaborate with domain experts and client stakeholders to solve data challenges across a variety of industries</li>
<li>Support and mentor other team members through code reviews, pair programming, and knowledge sharing</li>
<li>Lead internal sparring sessions and contribute to developing team-wide best practices and scalable project structures</li>
</ul>
Technologies you’ll use
Working with multiple clients, we are in touch with many technologies, which is truly exciting. We use state-of-the-art technologies while being fully pragmatic (we do not crack a walnut with a sledgehammer). We follow an ELT philosophy and divide the tasks between Data Engineering and Analytics Engineering accordingly.
The following technologies constitute our preferred data tech stack:
Data Loading
<ul>
<li>For our clients, we either use a scheduler (e.g. Apache Airflow or Prefect) and run Python DAGs with it - we also like to work with dlt as a framework</li>
<li>For standard connectors, we work with Fivetran or Airbyte Cloud preferably</li>
</ul>
Data Warehousing
<ul>
<li>For smaller data loads, we mostly use PostgreSQL databases</li>
<li>For larger datasets, we mostly work with Snowflake or BigQuery</li>
</ul>
Data Transformation
<ul>
<li>We love to use dbt (data build tool) since 2018 - we can also work without it, yet we are fans to be honest</li>
<li>It is important to us that we work version-controlled, peer-reviewed, with data testing, and other engineering best practices</li>
</ul>
Data Visualization
<ul>
<li>For smaller businesses with &lt; 100 FTE, we mostly recommend Metabase or Superset as a powerful open-source reporting tool</li>
<li>For specified needs and a centralized BI, we recommend PowerBI or Tableau</li>
<li>For a decentralized, self-service BI with more than 50 users, we recommend Looker, Holistics, or ThoughtSpot</li>
<li>We are always on the lookout for new tools, at the moment we are excited about Lightdash, Omni, dlt, and other tools</li>
</ul>
<h2 id="requirements">Requirements</h2>
We believe in a good mixture of experience and upside in our team. We are looking for both types of people equally - for this role, we require more expertise and proof of trajectory.
Besides that, we are looking for the following:
<ul>
<li>3–4 years of hands-on experience in data engineering or analytics engineering, with a strong focus on building and maintaining robust data pipelines and analytics-ready data models</li>
<li>Proficient in SQL and experienced with relational databases, capable of translating complex business logic into clear, maintainable queries</li>
<li>Hands-on experience using dbt (preferably dbt Cloud) in production environments, following best practices for modular, testable, and documented code</li>
<li>Solid understanding of data modeling techniques (e.g., Kimball dimensional modeling, Data Vault, star/snowflake schema) and data warehousing principles</li>
<li>Experience working with modern data stack tools, such as Snowflake, BigQuery, Airflow, Airbyte/Fivetran, Git, and CI/CD workflows</li>
<li>Proficient in Python (or a similar scripting language) for use cases such as API integration, data loading, and automation</li>
<li>Strong communication skills in English (written and spoken), with the ability to explain technical decisions and collaborate with both technical and non-technical stakeholders</li>
<li>Comfortable working in client-facing projects, navigating ambiguity, and delivering high-quality results with minimal oversight</li>
<li>Experience coaching or mentoring junior team members through code reviews, sparring, and knowledge sharing</li>
<li>Bonus: Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker) to support end-to-end workflows or assist analysts</li>
<li>Bonus: Fluency in German</li>
</ul>
<h2 id="benefits">Benefits</h2>
We are located in Berlin, close to Nordbahnhof. We are currently 20 colleagues and will grow to 22 colleagues this year. Other perks include:
<ul>
<li>We are a hybrid company that meets in the office twice a week - one common office day and one flexible day</li>
<li>We allow for intra-EU workcations for up to 3 months a year (extra-EU workcations also if this is allowed)</li>
<li>We have an honest, inclusive work environment and want to nurture this environment</li>
<li>We don’t compromise on equipment - a powerful Laptop, extra screens, and all the tools you need to be effective</li>
<li>We will surround you with great people who love to solve (mostly data) riddles</li>
<li>We believe in efficient working hours rather than long working hours - we focus on the output rather than the input</li>
<li>We learn and share during meetups, lunch &amp; learn sessions and are open to further initiatives</li>
<li>We pay a market-friendly salary and we additionally distribute at least 20% of profits to our employees</li>
<li>We are fast-growing and have technology at our core, yet we do not rely on a VC and operate profitably</li>
<li>We have a great yearly offsite event that brings us all together for a full week, enjoying good food, and having a good time (2021: Austria, 2022: Czech Republic, 2023+2024: Germany, 2025: Spain)</li>
</ul>
How you’ll get here
<ol>
<li>CV Screening</li>
<li>Phone/Coffee/Tea Initial Conversation</li>
<li>Hiring Test @home</li>
<li>Interviews with 2-3 future colleagues</li>
<li>Reference calls</li>
<li>Offer + Hired</li>
</ol>
Looking forward to your application :)

(Senior) Data & Analytics Engineer

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