QA Data Analyst: Pipelines, ETL & Dashboards

MED-EL Elektromedizinische Geräte Deutschland GmbH

Innsbruck

On-site

EUR 43,000 - 53,000

Full time

14 days+

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Job summary

MED-EL Elektromedizinische Geräte Deutschland GmbH in Innsbruck, Austria, is seeking a data‑driven professional to strengthen our data pipelines and analytics. You will design ETL/ELT workflows, optimize SQL queries, and develop BI dashboards to support process control and final product release. This role partners with QA, manufacturing, and IT teams.

Fluency in German and English is preferred. You will ensure data integrity, automate data tasks, and translate complex data concepts into clear

Qualifications

  • Experience designing end-to-end data pipelines and ETL/ELT workflows.
  • Proficient in high-level programming languages for data manipulation.
  • Hands-on expertise with BI platforms, RDBMS, SQL, and data cleaning/transformations.
  • Excellent analytical and problem-solving skills to translate data into business insights.
  • Strong German and English language skills.

Responsibilities

  • Write, optimize, and maintain complex relational database queries.
  • Design, build, and support scalable ETL/ELT data integration workflows.
  • Clean, transform, and model raw data for analytics.
  • Develop dashboards and reports for data-driven decisions.
  • Script automated data tasks and build data connectors to improve workflows.

Skills

SQL
ETL/ELT design
Python
BI tools
German language
English language

Education

Data engineering degree

Tools

BI platforms

Job description

MED-EL Elektromedizinische Geräte Deutschland GmbH in Innsbruck, Austria, is seeking a data‑driven professional to strengthen our data pipelines and analytics. You will design ETL/ELT workflows, optimize SQL queries, and develop BI dashboards to support process control and final product release. This role partners with QA, manufacturing, and IT teams.

Fluency in German and English is preferred. You will ensure data integrity, automate data tasks, and translate complex data concepts into clear

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