Design, develop, and maintain data pipelines that ingest, process, and deliver data from various sources, ensuring data quality and reliability
Data Modeling: Create and maintain data models to support reporting, analytics, and business intelligence needs, optimising structures for performance and efficiency
Implement ETL processes to transform raw data into meaningful insights, handling data transformation, aggregation and enrichment
Monitor and address data quality issues, implement data validation processes, and establish data governance practices
Manage and optimize data storage, processing, and distribution systems, ensuring scalability and performance
Collaborate with data scientists, analysts, and cross-functional teams to understand data requirements and deliver solutions that meet business needs
Document data engineering processes, pipelines, and systems to maintain clear and accessible knowledge for team members
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, or a related field
Minimum of 3 years of experience in data engineering or a related field
Proven experience with Redshift and Snowflake
Experience with DBT
Experience with Apache Airflow for workflow orchestration
Proficiency in Python for data pipeline development and scripting
Experience with AWS cloud services, including S3, EC2, and EMR
Familiarity with Kafka for real-time data streaming
Familiarity with data visualization and reporting tools (e.g. Tableau, Power BI or Looker)
Project management skills using Jira or similar tools
Ability to collaborate effectively with cross-functional teams and understand business data needs
Strong problem-solving skills, a proactive approach to troubleshooting data issues, and critical thinking abilities
Adaptable and open to learning new technologies and methodologies
Done for you
We'll apply to this for you
Denidel's HR team submits and tracks the application on your behalf.
