Data Engineer

Data Engineer

Responsibilities:

• Implement Data Pipelines: Build and integrate robust, scalable data processing pipelines for enterprise-level business analytics, ensuring high availability and performance.
• Database Schema & Modeling: Design and maintain efficient database schemas and data models that support complex business requirements and enable optimized querying.
• Data Lake & Warehousing: Manage and optimize data storage solutions within data lakes and warehouses (e.g., BigQuery), ensuring data integrity, accessibility, and cost-efficiency.
• Pipeline Automation & Monitoring: Develop automated monitoring, alerting, and self-healing features (including restartability and graceful failure handling) for all consumption pipelines.
• Troubleshooting & Data Quality: Proactively identify and resolve issues within source pipelines and data processing jobs; collaborate with Engineering teams to ensure data accuracy and quality.
• Collaboration: Partner with Business Analysts, Data Scientists, and Product Managers to define requirements and ensure cross-functional data usage and security standards are met.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience as a Data Engineer or in a similar data-focused role.
• Strong proficiency in programming languages such as Python or Java.
• Expertise in querying and managing relational and NoSQL databases (e.g., PostgreSQL, MongoDB).
• Hands-on experience with BigQuery and designing/maintaining scalable data lake architectures.
• Deep understanding of data warehousing concepts, ETL/ELT processes, and distributed systems.
• Experience with cloud platforms (Google Cloud Platform preferred) and big data technologies.
• Excellent problem-solving skills, with a strong analytical mindset to translate complex business needs into technical solutions.
• Strong communication and teamwork abilities to effectively collaborate across technical and non-technical teams.