
Netconomy GmbH
Data Engineer
Als Data Engineer bei NETCONOMY in Graz, Wien oder Pörtschach entwickelst du moderne, skalierbare Datenlösungen auf Google Cloud Platform im Data & AI Team.
Free. Atlas tailors your CV to exactly this role and keeps finding matching jobs for you.
Apply without optimisationThe Atlas advantage
- CV and cover letter written for exactly this role, not copied from a template.
- Match score with reasons Atlas shows you how well the role fits you and tells you honestly what fits and what doesn't.
- Everything in view tracking shows you where every application stands, from sending it to the interview.
Job description
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