Backend Engineer
Senior Data Engineer (GCP, Python, SQL, PySpark)
Bucharest
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Undelucram.ro on behalf of:
Adecco Romania
Our client is a global technology and digital transformation organization specializing in software engineering and IT consulting, serving international clients across multiple industries. The company operates in a fast-paced, collaborative environment, with a strong focus on innovation, engineering excellence, and continuous professional development.
About The Role
We are looking for a
Senior Data Engineer
to design and deliver scalable data pipelines and high-performance analytical solutions using SQL/BigQuery, Spark/PySpark, and Python on Google Cloud.
This role focuses on building reliable, cloud-native data products that enable advanced reporting, analytics, and decision-making across the organization
Mandatory Skills
- 5+ years of experience as a Data Engineer, building scalable data pipelines and working with cloud-based data ecosystems
- Expertise in SQL and hands-on experience building performant datasets in BigQuery or similar cloud data warehouses
- Proficiency in Python and PySpark for scalable data processing in distributed environments
- Understanding of data modeling, ELT/ETL patterns, and data quality best practices
- Familiarity with Google Cloud Platform, particularly BigQuery, Dataflow, and Cloud Composer, GCS, or equivalent cloud data services
- Background in building scalable data pipelines, both batch and near real-time, in a cloud-native environment
- Proficiency with version control, CI/CD pipelines, and automated testing frameworks
- Capability to troubleshoot and optimize performance across compute, storage, and processing layers
Nice-to-have Skills
- Experience with Infrastructure-as-Code, including Terraform, Ansible, and Chef
- Knowledge of shell scripting
- Experience in financial services or regulated environments
- Design and deliver batch and real-time ETL/ELT pipelines across cloud environments to support analytics and reporting
- Write and optimize advanced SQL transformations and build performant, cost-efficient BigQuery data models
- Implement scalable data processing solutions using Python and PySpark, ensuring maintainable and high-quality code
- Build robust data models and apply validation practices to maintain accuracy and reliability
- Use GCP services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub, and GCS to build and operate modern data platforms
- Troubleshoot complex pipeline issues and continuously improve compute, storage, and processing performance
- Collaborate with engineering, analytics, and business teams while contributing to CI/CD, code reviews, and testing standards
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