Fullstack Architect

As a Data Engineer, you will play a crucial role in designing, developing, and maintaining robust ELT pipelines using modern data engineering tools and practices. Your responsibilities will include: - Working with distributed, column-oriented databases such as Vertica and Snowflake to build high-performance data solutions. - Implementing and managing data workflows using orchestration tools like Apache Airflow. - Performing root cause analysis and troubleshooting data issues to ensure data integrity and availability. - Collaborating with cross-functional teams to understand data requirements and deliver scalable solutions. - Documenting data processes, workflows, and architecture for transparency and maintainability. To qualify for this role, you should have: - A Bachelor's degree in Computer Science, Engineering, or a related field. - 3+ years of hands-on experience with Python and SQL for data manipulation and transformation, Data Warehousing, Dimensional Modelling, and Data analytics. - Proficiency in AWS services for data storage, processing, and orchestration, ELT methodologies, and tools for data integration. - Familiarity with Apache Airflow, Jenkins, or similar orchestration/scheduling tools, CI/CD pipelines, and version control systems like Git. - Experience with distributed, column-oriented databases such as Vertica or Snowflake. - Strong analytical and problem-solving skills with a keen eye for detail, along with excellent communication and organizational skills. Preferred qualifications include: - A Master's degree in Computer Science, Engineering, or a related field. - Familiarity with data governance, security, and compliance best practices. - Knowledge of Apache Spark for distributed data processing and Apache Kafka for real-time data streaming.,