Data Engineer

Responsibilities:

• Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.
• Develops and maintains scalable databases, data pipelines, and builds out new API integrations to support continuing increases in data volume and complexity.
• Collaborates with science and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
• Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Writes unit/integration tests, contributes to engineering wiki, and documents work.
• Performs data analysis required to troubleshoot data related issues and assists in their resolution.
• Works closely with a team of frontend and backend engineers, product managers, and analysts.
• Defines company data assets (data models), data jobs (spark, sparkSQL, and hiveSQL, etc) to populate data models.
• Designs data integrations and data quality framework.

Top skills you need to have:

• BS or MS degree in Computer Science or a related technical field (or equivalent experience).
• 4+ years of SQL experience (No-SQL experience is a plus)
• 4+ years of experience with schema design and dimensional data modeling
• 4+ years of Python or Java development experience
• Experience developing with infrastructure as code (terraform, bicep, etc.)
• Ability in managing and communicating data warehouse plans to internal clients
• Experience designing, building, and maintaining data processing systems
• Experience working with either a Map Reduce or an MPP system on any size/scale
• Experience with or knowledge of Agile Software Development methodologies