Data Engineer

We are seeking an experienced and forward-thinking Data Engineer with hands-on expertise across Google Cloud Platform (GCP), Microsoft Azure, and AI-driven data solutions. The ideal candidate will design, build, and optimize scalable data architectures and pipelines that leverage cutting-edge technologies in cloud computing, machine learning, and automation. You will work closely with cross-functional teams (Data Science, AI/ML, and Cloud Infrastructure) to shape the next generation of data systems that enable intelligent, real-time, and predictive decision-making. Key Responsibilities: • Design, develop, and manage data pipelines, ETL/ELT processes, and data models across GCP and Azure environments. • Build real-time and batch data processing systems using modern frameworks and cloud-native services. • Collaborate with AI/ML teams to operationalize models and enable automated data-driven insights. • Implement data governance, quality, and security best practices across multiple cloud platforms. • Integrate and optimize data from diverse sources including APIs, IoT, streaming data, and unstructured formats. • Explore and adopt emerging technologies such as GenAI, MLOps, DataOps, Edge Computing, and LLM-based data engineering tools. • Leverage infrastructure as code (IaC) and CI/CD pipelines for scalable and automated deployments. • Continuously evaluate new technologies to enhance data platform capabilities and efficiency. Required Skills & Experience: • Strong proficiency in GCP (BigQuery, Dataflow, Pub/Sub, AI Platform) and Azure (Synapse, Data Factory, Databricks, Azure ML). • Hands-on experience with Python, SQL, and Spark for large-scale data processing. • Solid understanding of data warehousing, data lakes, and modern lakehouse architectures. • Experience with AI/ML integration, MLOps, and working with AI APIs or LLMs. • Proficiency with containerization and orchestration tools (Docker, Kubernetes, Airflow). • Familiarity with DevOps/DataOps principles and version control (Git, CI/CD pipelines). • Experience working in multi-cloud or hybrid environments. • Strong problem-solving skills and ability to work with emerging, fast-evolving technologies. Preferred / Nice-to-Have Skills: • Experience with GenAI platforms (Vertex AI, Azure OpenAI, LangChain, Vector Databases). • Knowledge of real-time analytics tools (Kafka, Flink, Kinesis). • Exposure to Edge AI, Serverless Computing, and Quantum-inspired data systems. • Certifications in GCP or Azure (e.g., Professional Data Engineer, Azure Data Engineer Associate).