
Senior Data Architect
7 days ago
Norla AB: A Global Leader in IT Consulting
Norla is a global leader in IT consulting, with a proven track record of delivering innovative solutions that drive business results. We are committed to staying at the forefront of technology trends, ensuring our clients remain competitive in today's fast-paced market.
We are seeking an experienced Senior Data Engineer to join our team as we continue to push the boundaries of what is possible. This key role will involve designing, building, and optimizing data pipelines on Google Cloud Platform (GCP). As a hands-on professional with deep technical expertise, you will collaborate closely with Data Scientists, ML Engineers, and other stakeholders to develop scalable and efficient data solutions that support advanced analytics and machine learning models.
Key Responsibilities
- Develop and maintain scalable, high-performance data pipelines on GCP.
- Work with both batch and real-time data processing solutions.
- Ensure data quality, consistency, and reliability across various sources.
- Optimize data models, query performance, and ETL/ELT processes.
- Automate workflows for data ingestion, transformation, and monitoring.
- Collaborate with Data Scientists and ML Engineers to provide clean, structured, and optimized data.
- Implement best practices for cost-effective, scalable data architectures on GCP.
- Leverage AI/ML-driven event correlation and predictive analytics to enhance data operations.
Qualifications & Experience
- Senior-level experience as a Data Engineer, working on large-scale data systems.
- Hands-on expertise with GCP services including BigQuery, Dataflow, Cloud Storage, Pub/Sub, Composer, etc.
- Strong programming skills in Python, SQL, and experience with orchestration tools like Airflow and Cloud Composer.
- Experience designing and optimizing ETL/ELT pipelines for structured and unstructured data.
- Familiarity with event-driven architectures, monitoring tools like Splunk and ServiceNow, and automation.
- Experience collaborating with Data Science and Machine Learning teams to support model training and deployment.
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