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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Netconomy - **Location:** Wien, Austria (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, BigQuery, Cloud Computing, Cloud Storage, Cluster Analysis, Computer Programming, Databases, Data as a Services, Data Architecture, Data Governance, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Visualization, Data Warehousing, Database Queries, Dimensional Modeling, Data Flow Control, Python (Programming Language), Metadata, Meta-Data Management, Power BI, SQL Databases, Data Streaming, Unstructured Data, Data Logging, Data Processing, Google Cloud, Real Time Systems, Data Ingestion, Cloud Monitoring, Google Data Studio, Pandas, Pyspark, Data Lineage, Machine Learning Operations, Terraform, Stream Processing, Looker Analytics, Software Version Control, Data Pipelines, Apache Beam - **Published:** September 25, 2026 - **Apply:** https://devjobs.at/team/netconomy/career ## About the Role * 3+ years of hands-on experience as a Data Engineer with proven expertise in Google Cloud Platform (GCP) * Strong experience with BigQuery (SQL, partitioning, clustering, optimization) and Dataflow (Apache Beam) * Strong programming skills in Python with experience in data manipulation libraries (PySpark, pandas) * Expert-level SQL proficiency for complex transformations, optimization, and analysis * Proficiency with Dataform for modular SQL-based data transformations and data pipeline management * Solid understanding of data warehousing principles, ETL/ELT processes, dimensional modeling, and data governance * Experience integrating data from various APIs and streaming systems (Pub/Sub) * Cloud Composer experience for workflow orchestration * Excellent communication and collaboration skills in English (min. B2 level) * Ability to work independently and as part of an agile team Beneficial Skills: * Google Professional Data Engineer certification * Knowledge of BigLake for unified access and management of structured and unstructured data * Experience with Dataplex for managing metadata, lineage, and data governance * Familiarity with Infrastructure-as-Code (Terraform) for automating GCP resource provisioning and CI/CD pipelines * Experience with data visualization tools such as Looker, Looker Studio, or Power BI * Interest in or experience with machine learning workflows using Vertex AI or similar platforms ## Description 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., * 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-optimized BigQuery 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary Austria](https://www.wearedevelopers.com/magazine/275-data-analyst-salary-austria) - [Got AI ideas but no money? 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