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

About the Job

Gemma Analytics helps clients to become more data-driven.

As one of our analytics engineers , you play a critical role in helping our clients generate business value out of their existing data sets. There are no two ways about it – you’re a Data Magician. While manipulating data, you bring out detailed information and quirky insights. You find what others can’t and glean business insights from numbers. By collaborating with clients, you find practical solutions to problems. You will get support and help from senior mentors in the first months.

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

Responsibilities:

• As we are tooling-agnostic, you will touch multiple technologies and understand the in’s & out’s what is currently possible in the data landscape.
• Collaborate and connect with domain experts to solve data obstacles in various industries.
• Develop advanced data reporting and visualizations.
• Apply data modeling methodologies and contribute to a robust data platform for our clients.

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.
• 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 mid-level role, we are looking for people with initial experience, and also with curiosity, openness to learning, and a structured mindset who are enthusiastic to solve numerical riddles while keeping in mind the business context.

Besides that, we are looking for the following:

• Experience with SQL and relational databases.
• Business Fluency (C2 or native) in German and English.
• First understanding of data modeling techniques (e.g. Data Vault or Kimball’s Dimensional Modelling) and data warehousing in general.
• Optional: Experience with one or more programming languages (Python preferred).
• Optional: Experience with one or more data visualization tools.
• Optional: Experience with managing stakeholders and/or clients.

Benefits

We are located in Berlin, close to Nordbahnhof. We are currently 18 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: Germany, 2024: Germany).

How you’ll get here

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

Looking forward to your application 🙂

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