Data Engineer

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.