
Senior Data Pipeline Specialist
4 days ago
A Data Engineer is responsible for designing, building, and maintaining scalable and secure data pipelines and infrastructure on GCP. This includes working with various GCP services like BigQuery, Dataflow, Cloud Storage, and Pub/Sub to create efficient data solutions.
Key responsibilities include developing ETL processes, implementing data governance practices, and ensuring data quality and accessibility.
Responsibilities
- Designing and Implementing Data Pipelines:
- Build and optimize data pipelines using GCP services like Dataflow, Dataproc, BigQuery, and Cloud Storage.
- Develop and implement Extract, Transform, Load (ETL) processes using tools like Python and PySpark.
- Data Modeling and Storage:
- Design and maintain data models, schemas, and documentation for efficient data storage and retrieval.
- Implement data governance policies, security best practices, and access control within GCP.
- Ensure data quality through testing, validation, and monitoring of data pipelines.
- Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
- Identify and resolve issues related to data pipelines and infrastructure, and optimize performance.
- Keep abreast of the latest trends and advancements in data engineering and GCP technologies.
Essential Skills
- Programming Languages:
- Strong proficiency in Python, SQL, and potentially Java.
- Hands-on experience with BigQuery, Dataflow, Cloud Storage, and other relevant GCP services.
- Familiarity with Hadoop, Spark, or Kafka is often preferred.
- Experience with data warehousing and data modeling techniques.
- Strong understanding of ETL processes and data pipeline development.
- Experience with Infrastructure as Code (IaC) using tools like Terraform is a plus.
- Experience with Continuous Integration and Continuous Deployment (CI/CD) pipelines.
- Excellent analytical and problem-solving skills.
- Ability to communicate effectively with technical and non-technical audiences.
Working at [Company Name]
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