Experience : 8+ Years
Location : Pune
Notice Period- Immediate to 30 days
Role Description :
We are looking a highly skilled and experienced Data Engineer to join our team. As a Data Engineer, you will play a critical role in designing, building, and scaling Google's massive data infrastructure and platforms. You will be a technical leader and mentor, driving innovation and ensuring the highest standards of data quality, reliability, and performance.
Responsibilities :
- Design and implement scalable, reliable, and efficient data pipelines and architectures across Google products and services.
- Develop and maintain data models, schemas, and ontologies to support a variety of data sources and use cases.
- Evaluate and recommend new data technologies and tools to improve infrastructure and capabilities.
- Collaborate with product managers, engineers, and researchers to define data requirements and deliver robust technical solutions.
- Build and optimize batch and real-time data pipelines using Google Cloud Platform (GCP) services such as Dataflow, Dataproc, Pub / Sub, and Cloud Functions.
- Implement data quality checks and validation processes to ensure consistency and accuracy.
- Design and enforce data governance policies to maintain data security and regulatory compliance.
- Design and manage scalable storage solutions with GCP services including BigQuery, Cloud Storage, and Spanner.
- Optimize data retrieval and storage strategies for performance and cost-efficiency.
- Implement data lifecycle management practices and archival strategies.
Required Skills :
Strong knowledge of data warehousing, data modeling, and ETL development.Proven expertise in designing and implementing large-scale data architectures and pipelines.Proficiency in SQL and at least one programming language such as Python or Java.Hands-on experience with GCP services like BigQuery, Dataflow, Dataproc, Pub / Sub, and Cloud Storage.Familiarity with open-source data tools like Hadoop, Spark, and Kafka.Excellent communication and collaboration skills.Good to Have :
Experience with data governance, data quality frameworks, and compliance.Exposure to machine learning and data science workflows.Experience with containerization and orchestration technologies such as Docker and Kubernetes.Contributions to open-source projects or technical communities.Google Cloud Professional Data Engineer certification.