We are looking for a skilled GCP Data Engineer to design, build, and optimize scalable cloud-native data platforms on Google Cloud Platform (GCP). The ideal candidate will have hands-on experience in developing high-performance data pipelines, integrating multiple data sources, implementing modern data warehouse solutions, and enabling advanced analytics.

You will collaborate with data architects, analysts, software engineers, and business stakeholders to deliver reliable, secure, and scalable data solutions that support enterprise reporting, AI/ML initiatives, and business intelligence.

Key Responsibilities:

- Design, develop, and maintain robust ETL/ELT pipelines using GCP-native services.

- Build scalable batch and real-time data ingestion frameworks.

- Develop and optimize data models for analytics and reporting.

- Work with structured, semi-structured, and unstructured datasets.

- Design enterprise-grade data lakes and cloud data warehouses.

- Build efficient solutions using BigQuery for large-scale analytical workloads.

- Develop data transformation pipelines using Dataflow, Apache Beam, and Cloud Composer (Airflow).

- Integrate multiple enterprise applications, APIs, databases, and third-party systems.

- Optimize SQL queries and improve overall pipeline performance.

- Implement data quality validation, monitoring, and reconciliation processes.

- Automate deployments using CI/CD pipelines.

- Collaborate with DevOps teams to deploy cloud-native data solutions.

- Monitor production jobs and troubleshoot pipeline failures.

- Implement logging, alerting, and performance monitoring.

- Ensure data security, governance, compliance, and access management.

- Work closely with business teams to understand reporting and analytical requirements.

- Participate in architecture discussions and recommend best practices.

Required Technical Skills:

- Google Cloud Platform (GCP)

- Strong hands-on experience with:

1. BigQuery

2. Cloud Storage

3. Dataflow

4. Pub/Sub

5. Cloud Composer (Apache Airflow)

6. Dataproc

7. Cloud Functions

8. Cloud Run

9. Cloud SQL

10. IAM

11. Secret Manager

12. Cloud Monitoring

13. Cloud Logging

- Programming

1. Python

2. SQL

Required Qualifications:

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

- 5+ years of experience in Data Engineering.

- Strong experience implementing cloud-based data engineering solutions.

- Hands-on expertise in Google Cloud Platform.

- Strong SQL development and query optimization skills.

- Experience building enterprise-scale ETL pipelines.

- Experience working with large datasets and distributed processing frameworks.

- Strong understanding of dimensional data modeling.

- Experience with Agile/Scrum methodologies.

- Excellent analytical and problem-solving skills.

- Good communication and stakeholder management skills.

- GCP Professional Data Engineer Certification.

- Experience with Terraform or Infrastructure as Code.

- Experience integrating ML pipelines with Vertex AI.

- Knowledge of Data Catalog and data governance tools.

- Experience with BI platforms such as Looker, Power BI, or Tableau.

- Familiarity with DataOps and MLOps practices.

- Exposure to real-time streaming analytics.