Data Pipeline Development: Design, develop, and maintain robust, scalable data pipelines to collect, process, and store structured and unstructured data from several data sources for the purposes of reporting and analytics.
Data Modeling and Architecture: Design and implement efficient data models and architectures to support analytical and reporting needs, ensuring data integrity, reliability, and performance.
Data Integration: Integrate data from various internal and external sources to ingest first, second and third-party data, including databases, APIs, and third-party platforms, while ensuring data quality and consistency.
Performance Optimization: Continuously optimize data pipelines and infrastructure for improved performance, scalability, and cost-effectiveness, leveraging cloud-based technologies and other frameworks.
Data Governance and Security: Implement and enforce data governance policies and security measures to protect sensitive data and ensure compliance with regulatory requirements.
Monitoring and Maintenance: Monitor data pipelines and systems for performance issues and errors. Proactively identify and resolve issues to ensure the reliability and availability of data infrastructure.
Documentation and Knowledge Sharing: Document data pipelines, architectures, and processes comprehensively. Share knowledge and best practices with team members to promote continuous learning and improvement.
Collaboration and Communication: Collaborate closely with cross-functional teams, including, BI, Product and other stakeholders, to understand reporting and analytics requirements and deliver technical solutions. Communicate technical concepts and solutions effectively to non-technical stakeholders.
