About the Position

Welcome on board, Titan

We are looking for a Data Engineer, who treats data as a first-class engineering discipline - someone who builds pipelines with the same rigour, testing, and craftsmanship that great software engineers bring to application code. You’ll work at the intersection of data and AI, designing and maintaining the data foundations that power machine learning models and analytical products for our clients. As a consultancy, no two projects look the same - one client might be on Databricks, the next on BigQuery, the one after that on something you’ve never heard of. If you care deeply about data quality, scalable architecture, and making messy real-world data actually useful, this role is for you.

The position is hired only within the EU / Fluency in Estonian, both written and spoken is strongly suggested / Mid-Senior level position

About MindTitan

We are a machine learning software and product development house working at the intersection of cutting-edge AI and practical software solutions. Headquartered in Estonia, our goal is to establish ourselves as Europe’s premier AI innovation center.

We’re a small, senior-heavy consultancy: no bloated org charts, no endless approval chains. Just a tight-knit team of sharp people solving hard problems for clients who care about the outcome. Every person here carries real weight, and if you have an idea for how we should grow or do things better, you’ll find an open door. We take that seriously.

Key Responsibilities

Design and build robust ETL/ELT pipelines that serve as the data foundation for AI and machine learning solutions;
Explore and implement agentic data engineering patterns where relevant - we’re an AI company and expect our data engineers to think beyond traditional pipelines;
Use dbt to transform raw data into clean, well-documented, and tested datasets;
Implement automated testing, monitoring, and alerting to ensure data integrity, reliability, and freshness across the entire pipeline lifecycle;
Work closely with AI/ML engineers and data scientists to design data architectures and feature pipelines;
Take messy, fragmented data from client source systems and turn it into structured, AI-ready assets built on sound modeling principles;
Ensure data solutions meet security and privacy requirements (GDPR and similar);
Some of the technologies you’ll work with: Databricks, dbt, BigQuery, SQL, Python, Airflow (or similar orchestration), Azure / AWS / GCP.

Requirements

3+ years of hands-on data engineering experience with production pipelines to show for it;
Good command of dbt: you know the difference between a well-structured project and a spaghetti DAG;
Solid experience with one data platform (Databricks, BigQuery or anything similar): you know its ecosystem well enough to have opinions about it;
Proficiency in Python and SQL for transformation and pipeline work;
Sound understanding of data modeling approaches such as Medallion Architecture, Dimensional Modeling, and Data Vault;
Comfortable with Git and CI/CD pipelines;
Ability to explain technical architecture decisions clearly to both internal teams and client stakeholders;
Excellent written and verbal English; Estonian is a strong plus;
Bonus points if you’re familiar with vector databases, web scraping, Elasticsearch, or just generally not panicking when you encounter a stack you’ve never seen before;
Located within EU.

We Offer

If you get bored, it's on you. We offer cutting-edge ML technologies and applications to work with
We trust you to do your work. Whether that’s in Tallinn or Tartu office, or mysteriously 'online' is up to you
We occasionally acknowledge each other's existence at team building events
Competitive compensation to finally afford that fancy keyboard you’ve been eyeing
Collaborative environment with minimal bureaucracy, unless we count daily standups
Career growth guaranteed, assuming we’re not orbiting a singularity already

About the Company

Flexibility without the fine print. Work when and where you’re most effective - no fixed 9-5, no micromanagement.

A culture built on trust. Responsibility is given by default. People feel safe speaking up, pushing back, and owning their work.

A team you’ll want to learn from. Small enough to know everyone, experienced enough that there’s always someone worth learning from.

A company still in motion. We’re growing thoughtfully which means your voice genuinely shapes where we go next.

Peek Behind the Scenes

We’re as serious about our coffee breaks as we are about our code quality.

Check more from our Instagram

Greetings from Your Future Team

”Better be prepared to tolerate the humor in our Slack discussions. It’s sometimes darker than Vantablack. Also, the proportion of people to dogs you can meet in the Tartu office is a cute side benefit. Please don’t apply if you don’t like animals.”

Zepp Uibo, Machine Learning Engineer

”First week at MindTitan: client calls and real tasks by day, colleague’s birthday party by night. The professional environment and varied projects keep advancing my skills, while the crew itself is genuinely cool. From the very first week, I’ve been welcomed with support and open arms.”

David Avedis Injarabian, Machine Learning Engineer

“I love it here. I haven’t just grown in leaps and bounds-I’ve grown in Star Trek–level light-speed jumps. The crew on board is absolutely the best, both in professional and personal level.

But before you join be warned: we like dark humour, wear Moomin socks and do serious stuff here, while wearing them.”

Kristjan Jansons

“Working in AI, there’s a high probability we know what we’re doing - give or take a confidence interval.

Good thing we also have a small crystal ball in our office for more precise predictions.”

Kristjan Jansons

“Here, growth isn’t just encouraged - it’s inevitable. You get to learn, experiment, and tackle challenges with a team that’s as sharp as they are funny. No idea is too bold, and no problem is faced alone. The real struggle in the beginning? Telling Sander and Madis apart!”

Merette Arula, Analyst-Project Manager

“Day one on the job, I got asked, ‘Do you know speech-to-text?’ I didn’t. ‘Want to learn?’ Absolutely. A few weeks later, we had a model more accurate for our needs than anything else out there.

We’re all about making things happen. Deploy a model in an unfamiliar system? Consider it done. Grab a beer after work? I’m already halfway through mine.”

Madis-Karli Koppel, Solutions Architect, Senior Machine Learning Engineer

Sounds Interesting? Say Hi!

If you are ready to join us (we are totally ready!), make sure to send us your CV together with your LinkedIn/Git profile and let’s talk!

Write to us at or fill out the form below.

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Data Engineer

Job Description, Responsibilities & Requirements