Title: Data Engineer Job Description: A Data Engineer is responsible for designing, building, and maintaining large-scale data systems and infrastructure. Their primary goal is to ensure that data is properly collected, stored, processed, and retrieved to support business intelligence, analytics, and data-driven decision-making. Key Responsibilities: 1. Design and Develop Data Pipelines: Create data pipelines to extract data from various sources, transform it into a standardized format, and load it into a centralized data repository. 2. Build and Maintain Data Infrastructure: Design, implement, and manage data warehouses, data lakes, and other data storage solutions. 3. Ensure Data Quality and Integrity: Develop data validation, cleansing, and normalization processes to ensure data accuracy and consistency. 4. Collaborate with Data Analysts and Business Process Owners: Work with data analysts and business process owners to understand their data requirements and provide data support for their projects. 5. Optimize Data Systems for Performance: Continuously monitor and optimize data systems for performance, scalability, and reliability. 6. Develop and Maintain Data Governance Policies: Create and enforce data governance policies to ensure data security, compliance, and regulatory requirements. Experience & Skills: 1. Hands-on experience in implementing, supporting, and administering modern cloud-based data solutions (Google BigQuery, AWS Redshift, Azure Synapse, Snowflake, etc.). 2. Strong programming skills in SQL, Java, and Python. 3. Experience in configuring and managing data pipelines using Apache Airflow, Informatica, Talend, SAP BODS or API-based extraction. 4. Expertise in real-time data processing frameworks. 5. Strong understanding of Git and CI/CD for automated deployment and version control. 6. Experience with Infrastructure-as-Code tools like Terraform for cloud resource management. 7. Good stakeholder management skills to collaborate effectively across teams. 8. Solid understanding of SAP ERP data and processes to integrate enterprise data sources. 9. Exposure to data visualization and front-end tools (Tableau, Looker, etc.). 10. Strong command of English with excellent communication skills.