Data Engineer (Data Engineering Team)

• 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.

• 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.

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.