data analysis

Data Architecture and Pipeline Development:

Design and develop scalable data warehousing solutions to handle increasing data volume and complexity

Build and maintain robust data pipelines using ETL/ELT methodologies and tools (AWS Glue, DBT, etc.)

Integrate data from various sources, including APIs, webhooks, and legacy systems

Collaborate with DevOps and Engineering teams to create and enhance data architectures

Data Quality and Governance:

Implement data validation, cleansing, and transformation processes to ensure data accuracy and consistency

Develop and implement data governance policies and procedures to maintain data integrity and security

Monitor data pipeline performance, identifying and resolving issues or bottlenecks proactively

Troubleshoot and resolve data extraction, loading, and transformation-related issues

Data Analysis and Visualization:

Perform data analysis for query optimization and performance improvements

Develop data quality dashboards and reports to monitor data health and identify trends

Utilize data visualization tools like Tableau or Looker to communicate insights effectively

Collaborate with business stakeholders to understand data requirements and translate them into technical specifications