Sr.DataEngineer

**Role Overview** We are seeking a skilled Data Engineer to design, build, and maintain scalable data platforms and pipelines across AWS and Azure. The role will support analytics, AI/ML, and business intelligence use cases using modern data technologies including Databricks, Snowflake, SageMaker, and Amazon Bedrock. The ideal candidate has strong cloud data engineering experience and collaborates closely with data scientists, analytics teams, and business stakeholders. **Key Responsibilities** Data Platform & Pipeline Development Design, develop, and optimize scalable, secure, and reliable data pipelines using batch and streaming patterns. Build and maintain ETL/ELT workflows ingesting data from structured and unstructured sources. Implement data transformations and orchestration using Databricks (Spark), SQL, and Python. Develop and maintain data models optimized for analytics and reporting. Cloud & Data Architecture Implement data solutions on AWS and Azure leveraging native services. Design and manage cloud storage solutions (e.g., S3, ADLS Gen2). Build cloud‑agnostic or hybrid architectures supporting multi‑cloud strategies when required. Optimize performance, scalability, reliability, and cost across platforms. Analytics & Data Warehousing Design and support Snowflake data warehouse solutions, including schema design, performance tuning, and cost management. Enable self‑service analytics and BI use cases through curated, high‑quality datasets. Partner with reporting and analytics teams to ensure data availability and accuracy. AI / ML & Advanced Analytics Enablement Support ML workflows by preparing and engineering features for SageMaker and Amazon Bedrock use cases. Collaborate with data scientists to operationalize ML models (MLOps integration). Enable GenAI and advanced analytics workloads through secure, governed data access. Data Quality, Security & Governance Implement data quality checks, monitoring, and validation frameworks. Ensure compliance with sec