Senior Data Engineer

Tabby is hiring a Senior Data Engineer for a remote role open to applicants in Serbia. Level rates it ; you can apply on Level.

AI in this role

Develop internal data services like feature stores and scalable data processing pipelines for a fintech platform.

pythonsqlairflowdebeziumbigqueryclickhousepostgresqlcockroachdbdockergitlabgcp

etldata-pipelinesfeature-storestreamingsystem-design

Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 25 million users choose Tabby to stay in control of their spending and make the most out of their money.

The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 70,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.
Tabby generates over $18 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region.

Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $6,5 billion.

We are hiring a Data Engineer for the Data Services Team who will help us create our internal solutions such as a Feature Store and will be ready to perform operational tasks.

Key Responsibilities:

Development Features store and other future data services;
Development EL / ELT / ETL pipelines;
Integration new tools for data processing and data storing;

Skills, Knowledge & Expertise:

3-5 years of experience as Data Engineer, ML Engineer, Backend Engineer;
Experience in developing high-load and scalable data processing and storage systems;
Good knowledge and background in event driving systems and streaming pipelines;
Python + best practice for Python;
SQL + best practice for SQL;
System design best practices;
Familiar with tech stack as Airflow, Debezium, BigQuery / Clickhouse, PostgreSQL / CockroachDB, Docker, GitLab(CI/CD), GCP;
REST API / GRPC API / Message brokers & Queues.

Bonus skills

GO development experience;
Experience on modern systems of data storing: Relational, MPP, NoSQL;
Experience on Google Cloud Platform.

How we rate this

Senior Data Engineer at Tabby rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Senior Data Engineer is an open job at Tabby.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Belgrade, / and is marked remote.
The job was posted on October 9, 2026.
Seniority: senior.
Applications are handled by Tabby. Apply on Tabby

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ETLData PipelinesFeature StoreStreamingSystem DesignPythonSQLAirflow

Questions you could be asked

Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?
Tell me about a project where feature store was part of your work. What did you do?
Tell me about a project where streaming was part of your work. What did you do?
Tell me about a project where system design was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ETL, Data Pipelines, Feature Store, Streaming, and System Design. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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