Intelliswift Software - Data Engineer - Google Cloud Platform

Data Engineer - Bangalore (Hybrid)

Position : Data Engineer

Experience : 7-12 Years

Notice Period : less than 15-20 days

Mode of Hiring : Permanent

Work Location : Bangalore (Hybrid

Must Have skills : Data Engineer, GCP, Big Query, Python, SQL, big data.

Job Requirement

Must Have skills :

1. Designing and implementing data pipelines and infrastructure

2. Proficiency in BigQuery and Cloud Storage

3. Experience with SQL for data processing

4. Understanding of data modeling concepts

5. Familiarity with ETL tools and techniques

6. Problem-solving ability in a distributed environment 7. Strong communication and collaboration skills

Primary Skills :

- SQL, BigQuery, python , Big Data, ETL, GCP

Job Description :

- We are seeking a skilled Data Engineer with expertise in Google Cloud Platform (GCP) and proficiency in BigQuery to join our team.

- The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and infrastructure to support our data analytics and machine learning initiatives.

- This role requires a deep understanding of GCP services, particularly BigQuery, as well as experience in data modeling, ETL processes, and cloud architecture.

Job Description :

1. Develop and optimize data pipelines in Google Cloud Platform (GCP) leveraging BigQuery for efficient data storage and processing.

2. Ensure data quality and integrity by implementing robust data validation and cleansing procedures within BigQuery.

3. Collaborate with cross-functional teams to understand data requirements and design scalable solutions using GCP services.

4. Monitor and troubleshoot data pipelines to ensure reliability, scalability, and performance, utilizing GCP monitoring tools.

5. Implement security best practices to safeguard sensitive data within BigQuery and other GCP services.

6. Continuously explore and adopt new technologies and techniques to enhance data engineering processes on GCP.

7. Document processes, procedures, and best practices for data engineering workflows on GCP, facilitating knowledge sharing and team collaboration