Data Engineer

Data Engineering & Modeling:

• Lead the development, optimization, and maintenance of complex data pipelines to handle large-scale data integration and transformation.
• Apply advanced SQL and Python to design, build, and optimize data processing systems and workflows.
• Utilize strong data modeling skills to develop and implement efficient and scalable database structures.
• Ensure data quality, accuracy, and security throughout all stages of data processing.

Cloud Data Solutions:

• Work extensively with cloud platforms (e.g., AWS, Azure, Google Cloud) to design and deploy scalable data solutions.
• Implement cloud-based data lakes, warehouses, and other data storage solutions in collaboration with data architects and cloud engineers.
• Automate and optimize cloud infrastructure to enhance performance and reduce costs.

Machine Learning & AI Support:

• Support data scientists and machine learning engineers by preparing data for machine learning and AI models.
• Utilize basic knowledge of machine learning concepts to identify opportunities for predictive analytics and automation within data workflows.

Data Visualization:

• Provide clean, structured data to business stakeholders for use in visualizations with Power BI, Tableau, QuickSight, and other tools.
• Collaborate with analysts and business users to deliver data that meets their reporting and analytics needs.

Collaboration & Leadership:

• Mentor junior data engineers and provide technical leadership in designing data solutions.
• Work closely with cross-functional teams including data scientists, cloud architects, and business analysts to ensure data strategies align with business objectives.
  • Troubleshoot, optimize, and resolve issues in existing data infrastructure and pipelines.