Senior GCP Data Engineer

We are seeking an accomplished Senior GCP Data Engineer to join our Engineering department and lead the design, development, and optimization of large-scale data solutions on Google Cloud Platform. In this role, you will shape our data architecture, champion best practices, and collaborate with cross-functional teams to transform complex data into actionable insights that drive business value.

Responsibilities:

1. Design, build, and maintain scalable data pipelines on GCP using BigQuery, Dataflow, Dataproc, Pub/Sub, and other native services.
2. Develop high-performance ETL/ELT workflows in Python and PySpark, ensuring data quality, reliability, and consistency across the platform.
3. Architect and optimize data warehouse solutions in BigQuery, including partitioning, clustering, and performance tuning for large datasets.
4. Implement workflow orchestration and job scheduling through Apache Airflow, ensuring timely and reliable data delivery.
5. Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver robust, reusable data models.
6. Define and enforce data governance, security, and compliance standards across all data workflows and storage layers.
7. Monitor, troubleshoot, and resolve performance bottlenecks, ensuring high availability and fault tolerance of data infrastructure.
8. Mentor junior engineers and promote best practices in coding, testing, and DevOps for data engineering projects.

Requirements:

1. 8–15 years of professional experience in data engineering,



with at least 4 years working extensively on Google Cloud Platform.
2. Expert proficiency in GCP services such as BigQuery, Pub/Sub, Dataflow, Dataproc, Cloud Storage, and Cloud Composer (Airflow).
3. Solid programming skills in Python, with hands-on experience developing distributed data processing jobs using PySpark.
4. Proven track record in architecting and optimizing large-scale data warehouses and data lakes, including schema design and performance tuning.
5. Solid understanding of ETL/ELT frameworks, data integration patterns, and stream/batch processing paradigms.
6. Experience implementing CI/CD pipelines, infrastructure-as-code, and automated testing for data engineering solutions.
7. Deep knowledge of data security, governance, and compliance best practices in cloud environments.
8. Excellent problem-solving abilities, communication skills, and the ability to work in agile, cross-functional teams.

Nice to Have:

1. GCP Professional Data Engineer or Architect certification.
2. Familiarity with infrastructure-as-code tools such as Terraform or Cloud Deployment Manager.
3. Exposure to machine learning pipelines and feature engineering on GCP AI/ML services.
4. Experience with real-time streaming technologies like Apache Kafka or Confluent Platform.
5. Knowledge of data catalog solutions (e.g., Google Data Catalog) and data lineage tooling.
6. Background in domain-driven design and microservices architecture.
7. Understanding of cost optimization strategies for cloud data platforms.
8. Contributions to open-source data engineering projects or active participation in technical communities.

📌 GCP Data engineer (Pune)
🏢 Globant
📍 Pune