Senior Data Engineer Data Analytics

I. Data Engineering • Design, implement, and optimize ETL/ELT pipelines to transform raw data into usable formats. • Develop and maintain data lakehouse using modern cloud platforms such as Microsoft Fabric, Azure Synapse or Databricks. • Ensure data pipelines are scalable, efficient, and fault-tolerant. II. Data Architecture • Collaborate with data architects to design data models and schemas for analytics and reporting. • Implement data governance, security, and compliance practices. • Integrate diverse data sources (structured, semi-structured, and unstructured) into unified data platforms. III. Performance Optimization • Monitor and improve the performance of data pipelines and database systems. • Optimize storage, compute, and data querying to enhance cost-efficiency on cloud platforms. • Address bottlenecks and implement proactive maintenance strategies.IV. Collaboration & Leadership• Work closely with data analysts, BI developers, and data scientists to understand business requirements. • Mentor junior data engineers and contribute to building a high-performing engineering team. • Provide technical guidance and best practices for data engineering processes. IV. Continuous Improvement • Stay up-to-date with the latest trends in data engineering, analytics, and cloud technologies. • Propose and implement new tools and frameworks to improve workflows and scalability. • Participate in code reviews, knowledge sharing, and team-building initiatives.