- Design, develop, and maintain robust data warehouse solutions to support business intelligence and analytics needs.
- Design, implement and manage metadata frameworks to ensure data consistency and quality.
- Develop and maintain reference data and dimensional data models to support various business processes.
- Design and implement ETL (Extract, Transform, Load) processes using tools like SnapLogic or Informatica to integrate data from multiple sources.
- Utilize Python for data manipulation, automation, and integration tasks.
- Optimize the performance of data systems and processes.
- Implement transformations in DBT (Data Build Tool) to streamline data workflows.
- Collaborate with cross-functional teams to develop and maintain reporting tools and dashboards.
- Implement data governance practices to ensure data integrity, security, and compliance.
- Stay updated with the latest advancements in Generative AI and explore opportunities to integrate AI solutions into data engineering processes.
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- 8 to 10 years of experience in working with data platforms
- Strong knowledge of data warehouse concepts, metadata frameworks, reference data, and dimensional data modeling.
- Proficiency in ETL processes and tools like SnapLogic or Informatica.
- Advanced skills in Python programming.
- Experience with databases such as SQL Server, PostgreSQL, and Snowflake.
- Advanced SQL knowledge.
- Experience with reporting tools such as Tableau, Power BI, or similar.
- Understanding of data governance principles and best practices.
- Knowledge of Generative AI and its applications is a plus.
- Experience with DBT (Data Build Tool) for data transformations.
- Ability to optimize the performance of data systems and processes.
- Excellent problem-solving skills and attention to detail.
- Solid communication and collaboration skills.