Job Description
Job Description:
Basic Qualifications
- Experience: Minimum of 12+ years in data management, data engineering, or related fields, with 5-7 years in a dedicated data engineering or data architecture role.
- Data Modeling and Architecture: Proven experience in designing and implementing data architectures for scalability and performance, including dimensional modeling and schema design and in Datawarehousing projects
- SQL Proficiency: Advanced knowledge of SQL for data querying, transformation, and database management tasks.
Required Skills
- Data Warehousing: Hands-on Datawarehousing solutions preferrable on cloud data warehousing platforms, such as AWS Redshift or Snowflake, with at least one completed project showcasing independent implementation.
- ETL Development: Proficiency in building and managing ETL workflows using platforms such as Informatica, AWS Glue or other SQL-based ETL tools.
- Database Management and Optimization: Strong skills in database management, query optimization, and performance tuning for large datasets.
Desired Qualifications
- Data Transformation and Processing: Expertise in data cleansing, transformation, and structuring techniques to prepare data for analytics solutions
- Cloud Computing and Infrastructure: Working knowledge of key AWS services (e.g., S3, Lambda, and Glue), with a focus on integrating these services within a scalable data architecture.
- Project Management: Demonstrated ability to independently manage data engineering projects, from planning and design to execution and optimization.
- Advanced Data Warehouse Concepts: Familiarity with best practices for data warehousing, including star and snowflake schemas, and experience in implementing data marts or data lakes.
Nice-to-Have Skills
- Data Security and Compliance: Understanding of data security practices, including encryption, access control, and compliance, particularly in cloud environments.
- Business Intelligence and Reporting: Basic exposure to BI tools such as Power BI, with an understanding of how data architectures support dashboard and reporting needs.
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