Data Engineer

Data Pipeline Development

• Design, develop, and maintain scalable and reliable data pipelines to ingest, process, and store large volumes of data from various sources.
• Implement data workflows using ETL (Extract, Transform, Load) processes to ensure data quality and integrity.

Data Integration and Management

• Collaborate with data architects, product owners, business analysts, and other stakeholders to understand data requirements and deliver data solutions that meet their needs.
• Integrate data from multiple sources, including databases, APIs, and external data providers, into a unified data platform.
• Manage and optimize data storage solutions, ensuring efficient data retrieval and processing.

Data Quality and Governance

• Implement data quality checks and validation processes to ensure the accuracy and consistency of data.
• Adhere to data governance policies and best practices to maintain data security and compliance.

Performance Optimization

• Monitor and optimize data pipeline performance to ensure timely and efficient data processing.
• Identify and resolve performance bottlenecks and system issues to maintain data pipeline reliability.

Documentation and Collaboration

• Document data engineering processes, workflows, and solutions for future reference and knowledge sharing.
  • Collaborate with cross-functional teams to support data-driven decision-making and project initiatives.