
Data Architect and Engineering Professional
4 days ago
Globally renowned financial institutions seek highly skilled professionals to spearhead their cloud data engineering endeavors.
The ideal candidate will be responsible for architecting and implementing cutting-edge data pipelines using Google Cloud Platform (GCP) services, orchestrating workflows with Apache Airflow, automating tasks with Jenkins builds, managing and processing large datasets using Pyspark, Dataflows, and Dataproc, integrating with Restful or GraphQL APIs, designing RESTful API endpoints, and maintaining comprehensive documentation of all data components.
- Design and deploy scalable data pipelines leveraging GCP services such as BigQuery, Dataflow, and Dataproc.
- Orchestrate complex workflows using Apache Airflow, automate repetitive tasks using Jenkins builds, and streamline data processing pipelines.
- Manage and process massive datasets utilizing Pyspark, Dataflows, and Dataproc, ensuring seamless integration with various APIs and CI/CD pipelines.
- Develop and maintain RESTful API endpoints, integrate with existing systems, and design efficient data architectures.
- Create and maintain detailed documentation of data components, including logical and physical data models, database objects, and administration best practices.
The successful candidate should possess at least 6+ years of experience in data engineering, with expertise in BigQuery, Pyspark, Dataflows, Dataproc, Apache Airflow, and Java or Python programming languages.
A strong background in data architecture, ingestion, and ETL processes is essential, along with prior experience working in the financial or banking industry.
This is a remote position requiring local presence in Gurgaon, India. The contract duration is 12 months.
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