Mid-Level Data Engineer

2 days ago

Budapest, Budapest, Hungary OnHires Full time
Highlights
  • Remote-first role open to candidates from Brazil / South America, Turkey, and Northern Africa
  • Work on a data-driven SaaS platform focused on large-scale web data collection and automation
  • Location: Remote — preferred: Europe time zone (Eastern Europe, Turkey, Tunisia). Brazil as alternative.
About Our Client (for Engineers)

Our client is a remote-first SaaS product company based in Berlin, building data-intensive solutions that power advanced analytics and operational decision-making.
They work with complex, high-volume data flows and rely on a modern, well-structured engineering stack to keep things reliable, transparent, and scalable.

What makes this environment attractive for engineers:

  • You work end-to-end with real data products, not abstract pipelines.

  • You collaborate with a small, experienced team that values clean code, simplicity, and engineering discipline.

  • You use modern tooling — Python, Prefect, SQL, Metabase, cloud services — without legacy overload or bureaucratic overhead.

  • You get clear requirements, manageable scope, and the ability to make meaningful improvements.

  • You grow by solving practical, non-trivial data challenges that directly impact the product.

Role Overview

This is a mid-level role designed for engineers who already have solid Python + ETL experience and want to deepen their expertise with workflow orchestration, data quality, and modern BI tooling.

You will build reliable pipelines, improve data accuracy, and support the team in turning raw data into clean, usable datasets and dashboards.
You won't be expected to lead projects or mentor others — but you must be able to independently handle well-defined engineering tasks.

Responsibilities

You will work alongside senior engineers and product stakeholders to maintain and evolve the data platform. Your work will include:

ETL & Data Pipelines

  • Develop and maintain ETL pipelines using Python and Prefect

  • Write clean, tested code for transformations, ingestion jobs, and integrations

  • Optimize pipeline performance and reliability

Data Quality

  • Implement validation rules, sanity checks, and lightweight monitoring

  • Investigate and resolve data issues in collaboration with the team

  • Contribute to improving data consistency and transparency

Data Modeling & Analytics

  • Help develop new data models and contribute to schema design

  • Build and maintain dashboards in Metabase to support internal stakeholders

  • Support analytical reporting by preparing clean datasets

Collaboration

  • Translate business requirements into clear engineering tasks

  • Document your work and follow internal best practices

  • Communicate effectively with engineering, product, and business teams

Your ProfileMust Have

  • 3–5+ years in Data Engineering or Python Engineering

  • Strong proficiency in Python (pandas, SQLAlchemy, typing, testing)

  • Hands-on experience with ETL orchestration (Prefect preferred; Airflow acceptable)

  • Solid SQL skills and familiarity with relational databases

  • Experience with data quality checks, validation, or monitoring

  • Experience with Metabase or similar BI tools

  • Understanding of cloud-based data workflows (AWS, GCP, or Azure)

  • Ability to work independently on assigned tasks

  • English proficiency and clear communication

Nice to Have

  • dbt or similar transformation tools

  • Experience with NoSQL databases

  • Basic analytics or statistics knowledge

  • Exposure to APIs or light backend work

  • Experience in distributed remote teams

What Our Client Offers

  • Work in a small, senior, engineering-driven environment

  • Fully remote culture with flexible hours

  • Modern stack (Python, Prefect, SQL, Metabase, AWS/GCP/Azure)

  • Real opportunity to deepen ETL & data quality expertise

  • Competitive compensation depending on location

  • Personal development support

  • Optional office access on the tech campus near Berlin

  • Regular virtual and onsite team meetups


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