Job Description :

We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms on Google Cloud Platform. You will work with engineering, analytics, and business teams to ensure data is reliable, accessible, and optimized for downstream use cases.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).

- Build and manage batch and real-time data processing workflows.

- Develop data ingestion, transformation, and integration solutions across multiple data sources.

- Work with BigQuery to design data models, optimize queries, and improve data warehouse performance.

- Build ETL/ELT pipelines using services such as Dataflow, Dataproc, Cloud Composer, and Pub/Sub.

- Manage and process data stored in Google Cloud Storage.

- Ensure data quality, consistency, security, and reliability across data platforms.

- Monitor and troubleshoot data pipelines and production workflows.

- Optimize cloud infrastructure and data processing workloads for performance and cost.

- Collaborate with data scientists, analysts, software engineers, and business stakeholders.

- Implement CI/CD and automation practices for data engineering workflows.

- Maintain technical documentation for data pipelines, architecture, and processes.

Required Skills :

- Strong hands-on experience with Google Cloud Platform.

- Experience with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.

- Strong programming skills in Python.

- Strong proficiency in SQL.

- Experience designing and building ETL/ELT pipelines.

- Good understanding of data warehousing, data modeling, and distributed data processing.

- Experience working with large-scale structured and unstructured datasets.

- Knowledge of Apache Beam, Spark, or similar data processing frameworks.

- Familiarity with Git and version control.

- Strong problem-solving and debugging skills.

Good to Have :

- Experience with Apache Airflow.

- Knowledge of Terraform or Infrastructure as Code.

- Experience with Docker and Kubernetes.

- Familiarity with Kafka or other streaming technologies.

- Exposure to dbt.

- Experience implementing data governance and data security practices.

- Knowledge of GCP IAM, networking, and cloud security.

- Google Cloud certification such as Professional Data Engineer.