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Netconomy GmbH

Data Engineer

Wien

AI & DataData EngineeringStartup

Als Data Engineer bei NETCONOMY in Graz, Wien oder Pörtschach entwickelst du moderne, skalierbare Datenlösungen auf Google Cloud Platform im Data & AI Team.

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Atlas Vorteil

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Stellenbeschreibung

Over the past 25 years, NETCONOMY has grown from a startup into a team of 500 people across 10 European locations. We believe in the power of agile and cross-functional collaboration, bringing together people from diverse backgrounds to build outstanding digital solutions.

YOUR JOB

As a Data Engineer, you’ll play a key role in building modern, scalable, and high-performance data solutions on Google Cloud Platform (GCP). You’ll be part of our growing Data & AI team, designing and implementing data architectures that help clients unlock the full potential of their data.

Your job's key responsibilities are:

  • Building efficient and scalable ETL/ELT processes to ingest, transform, and load data from various structured and unstructured sources (databases, APIs, streaming platforms) into BigQuery and Cloud Storage
  • Implementing data ingestion and real-time processing using Dataflow (Apache Beam) and Pub/Sub for batch and streaming workflows
  • Developing SQL transformation workflows with Dataform, including version control, testing, and automated scheduling with built-in quality assertions
  • Creating efficient, cost-optimizedBigQuery queries with proper partitioning, clustering, and denormalization strategies
  • Orchestrating complex workflows using Cloud Composer (Apache Airflow) and Cloud Functions for event-driven data processing
  • Implementing centralized data governance and metadata management using Dataplex with automated cataloging and lineage tracking
  • Monitoring and optimizing data pipelines for performance, scalability, and cost using Cloud Monitoring and Cloud Logging
  • Collaborating with data scientists and analysts to understand data requirements and deliver actionable insights
  • Staying up to date with GCP advancements in data services, BigQuery features, and data engineering best practices