Principal Data Engineer

4 days ago

India Nexuspoint Consultant Full time

Job Title: Principal Data Engineer Contract Period:  more than 6 months Experience:  6+ Working hours:  9:30am to 6:30pm IST About the Role We are looking for an accomplished Principal Data Engineer to lead the ideation, architecture, design and development of our next-generation enterprise data platform. This role requires a visionary technologist with deep hands-on expertise in cloud data engineering (GCP preferred), data architecture, and software engineering. You will work closely with cloud, security, and infrastructure architects to ensure seamless alignment with the organization's broader technology and business strategies. Key Responsibilities: Lead the end-to-end architecture and development of a modern enterprise-scale data platform from the ground up. Collaborate with cloud and security architects to ensure platform scalability, performance, and compliance. Architect, design, and implement batch and real-time streaming data infrastructures and workloads. Build and maintain data lakehouse architectures within the GCP ecosystem. Design and develop connector frameworks and reusable data ingestion pipelines to source data from both on-premises and cloud systems. Architect and implement metadata management, including data catalogs, lineage, quality, and observability frameworks. Design and develop data quality frameworks and governance processes to ensure reliability and accuracy. Develop microservices-based components using Kubernetes, Docker, and Cloud Run to abstract platform and infrastructure complexities. Design and optimize data storage, transformation, and querying performance for large-scale datasets while ensuring cost efficiency. Implement observability tooling (Grafana, Datadog) and DataOps best practices, including CI/CD and test automation. Collaborate with data scientists and analysts to define data models, schemas, and advanced analytics capabilities. Drive deployment, release management, and platform scalability initiatives. Stay ahead of emerging data engineering trends, tools, and best practices to continuously evolve the platform. Required Skills & Experience 6+ years of proven experience in modern cloud data engineering and enterprise data platform architecture. Demonstrated success in architecting and delivering large-scale greenfield data platform projects. Deep expertise in Google Cloud Platform (GCP) and its ecosystem — BigQuery, Cloud Functions, Cloud Run, Dataform, Dataflow, Dataproc, SQL, Python, and Airflow. Strong understanding of streaming technologies such as Kafka or Pub/Sub. Hands-on experience with microservices architectures using Kubernetes, Docker, and Cloud Run. Proven ability to design semantic layers and metadata-driven architectures. Expertise in data modeling, data architecture, and data governance principles. Experience with observability and monitoring tools (Grafana, Datadog). Strong understanding of DataOps principles, including automation, CI/CD, and testing for data pipelines. Experience architecting secure, scalable, and high-performance data solutions.

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