BI Full Stack Developer

Description

At INNIO we offer you

• Young & supportive team - in a fast-growing international business environment
• Learn & develop yourself - help you craft your career path with (INNIO learning, free language courses according to business needs
• Hybrid working - 50% Office, 50 % Home Office with flexible working hours
• Cafeteria package with various options - SZÉP Card, Cash option, Nursery & kindergarten support
• Medicover Spring White Package- from the first day of employment
• Easily accessible location - in the heart of the most vibrant campus area in Budapest (location: 13rd District, easy to approach by Metro Line 3)
• Take a break - Recharge your batteries with free coffee and tea selection in the kitchen area
• Live an active lifestyle – activate your AYCM pass

We are looking for a BI Full Stack Developer with a strong backend foundation to join our multinational BI team. This role focuses on technical integration and reliability across the BI stack. You will work closely with Data Engineers and Tableau Frontend BI Professionals to ensure that analytical data is reliable, well-modeled, and fit for business-facing consumption.

You will act as a technical copilot — validating data in Databricks, shaping analytical datasets using SQL, enabling automation with Python, and guiding frontend colleagues on how to consume data effectively and efficiently.

How This Role Fits in the Team

• Tableau Frontend BI Professionals

Own business-facing delivery, storytelling, and stakeholder communication.

• BI Full Stack Developer (this role)

Own technical integration, data reliability, and cross-layer BI decisions.

• Data Engineers

Own raw data ingestion, core pipelines, and platform-level engineering.

• You sit in the middle of the BI delivery chain, ensuring data can safely and efficiently flow from Databricks to production dashboards.

Your tasks

Data Reliability & Validation (Databricks)

• Validate analytical datasets in Databricks to ensure correctness, consistency, and readiness for BI consumption.
• Test data reliability across different sources, refresh cycles, and edge cases.

SQL-Based Data Integration & Modeling

• Design and implement SQL-based transformations for analytical datasets.
• Consolidate data from multiple sources into BI-ready datasets optimized for Tableau consumption.

Automation & Backend Enablement (Python)

• Use Python for automation and backend BI workflows, such as: PySpark-based data processing, dbt models and tests, Dagster-based orchestration.
• Reduce manual BI workload through automation, monitoring, and repeatable processes.

Technical Enablement for Frontend BI

• Advise Tableau Frontend BI Professionals on:
• Which datasets and tables to use for specific analytical use cases
• How to structure queries and filters for performance and scalability
• Act as a technical reviewer for BI use cases before and during frontend development.

Cross-Team Collaboration & Standards

• Collaborate closely with Data Engineers and BI Frontend professionals throughout the BI delivery lifecycle.
• Contribute to BI technical standards, continuous improvement, documentation, and best practices.

Your Profile

Strong Backend BI Foundation (must-have)

• Intermediate/Advanced SQL (complex joins, aggregations, case logic, window functions, etc).
• Hands-on experience validating and working with analytical data in Databricks or other cloud-based platforms.
• Solid understanding of analytical data modeling and how Tableau consume data.

Python & Automation

• Practical experience using Python for data processing or automation.
• Familiarity with tools and frameworks such as PySpark, dbt, Dagster, or similar.
• Ability to design backend BI solutions with frontend performance and usability in mind.

Nice-to-Have Skills

• Experience with Delta Lake, Unity Catalog, or Databricks SQL.
• Experience with Tableau/Power BI dashboards.
• Familiarity with data governance, testing, or monitoring practices.
• Familiarity with version control (git init, git add, git commit, git push, git pull, git checkout).