Full-Time Staff Data Engineer

As a Staff Data Engineer, you'll build and optimize data infrastructure to enable strong data-driven decision-making.

You'll use cutting-edge technologies, lead complex projects, and collaborate with cross-functional teams to create scalable data solutions.

1. Data Engineering Leadership:
2. Lead the design and implementation of high-performance data pipelines and workflows using Databricks on AWS.
3. Drive innovation and improvements in data engineering practices and processes.

1. Data Warehouse Development & Optimization:
2. Develop, maintain, and optimize the data warehouse architecture for performance, scalability, and reliability.
3. Collaborate with data scientists and analysts to ensure the warehouse supports business intelligence and machine learning needs.

1. ETL Pipeline Development:
2. Design and build ETL processes to integrate, transform, and deliver data from multiple sources.
3. Ensure ETL jobs are optimized for efficiency, accuracy, and timeliness.

1. Data Quality & Monitoring:
2. Implement tools and frameworks to monitor data accuracy, consistency, and reliability.
3. Build automated systems to detect and resolve data quality issues.

Collaboration & Mentorship:

• Partner with cross-functional teams (engineers, product managers, stakeholders) to understand data needs and deliver solutions.
• Provide technical guidance and mentorship to junior engineers.

System Performance & Troubleshooting:

• Continuously monitor data platform performance, identifying and addressing bottlenecks.
• Act as a technical expert to resolve complex data engineering challenges.

Documentation & Best Practices:

• Create and maintain documentation for pipelines, processes, and system configurations.
• Advocate for best practices in coding standards, data governance, and security.

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