- Develop and automate Python scripts for data processing and transformation.

- Design, implement, and manage data pipelines to facilitate seamless data integration and flow.

- Utilize GCP services, particularly BigQuery and Cloud Functions, to support data processing needs.

- Create and optimize advanced SQL queries for efficient data retrieval and manipulation in BigQuery.

- Collaborate with cross-functional teams to gather requirements and implement data solutions.

- Work with Apache and Databricks to enhance data processing capabilities.

A Google Cloud Platform (GCP) Data Engineer job involves 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.

Key Responsibilities :

Designing and Implementing Data Pipelines :

- Build and optimize data pipelines using GCP services like Dataflow, Dataproc, BigQuery, and Cloud Storage.

ETL Processes :

- 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.

Data Governance and Security :

- Implement data governance policies, security best practices, and access control within GCP.

Data Quality and Monitoring :

- Ensure data quality through testing, validation, and monitoring of data pipelines.

Collaboration and Communication :

- Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.

Troubleshooting and Optimization :

- Identify and resolve issues related to data pipelines and infrastructure, and optimize performance.

Staying Updated :

- 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.

- GCP Services : Hands-on experience with BigQuery, Dataflow, Cloud Storage, and other relevant GCP services.

- Big Data Technologies : Familiarity with Hadoop, Spark, or Kafka is often preferred.

- Data Modeling and Warehousing : Experience with data warehousing and data modeling techniques.

- ETL and Data Pipelines : Strong understanding of ETL processes and data pipeline development.

- Cloud Infrastructure : Experience with Infrastructure as Code (IaC) using tools like Terraform is a plus.

- CI/CD : Experience with Continuous Integration and Continuous Deployment (CI/CD) pipelines.

- Problem-Solving : Excellent analytical and problem-solving skills.

- Communication : Ability to communicate effectively with technical and non-technical audiences.