Data Engineer

Responsibilities:

• Designs, implements, integrates, and tests complex infrastructure and software solutions.
• Monitor database performance and implement optimization techniques to improve database performance.
• Provides technical leadership and mentorship for other team members.
• Reviews and critiques designs and implementations.
• Writing high-quality, efficient, and maintainable code, often with a focus on solving complex technical challenges.
• Facilitates collaboration of working team and often engages with stakeholders and product owners.
• Identifying and addressing performance bottlenecks, and optimizing code and systems for improved speed and efficiency.
• Maintaining comprehensive technical documentation, including system architecture, code comments, and documentation to assist in understanding and maintaining the software.
• Effectively communicating technical concepts and project status to non-technical stakeholders.

Requirements:

• Expert-level knowledge of Snowflake is a must.
• Knowledge of other data warehouse products is an added advantage.
• Degree in Computer Science, Information Systems, or equivalent experience.
• 8+ years of related professional experience.
• Advanced knowledge in multiple areas of:
• data transformations, data pipelines, workflow automation, and scheduling systems
• data-centric systems architecture
• database systems, data warehouses, distributed file storage and compute platforms

Experience with several of the technologies we currently use:

• Cloud Providers: AWS, Azure.
• Data Pipelines: Apache Airflow, debt.
• Data Tools: Pyspark, Snowpark, AWS Glue, Pandas, Databricks, SageMaker.
• Databases: Snowflake, SqlServer, Postgresql.
• Containerization: Kubernetes, Docker.
• Languages: Python, C#, Golang, Bash, SQL.
• CI/CD: GitLab, Azure DevOps.
• SCM: Git, Github, GitLab.