(Senior) Data & Analytics Engineer

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 :)