Data Engineer (Data Engineering Team)

Responsibilities: • 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, optimizing data 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.