Pixel Insights Data Engineer

Minimum qualifications:

• Bachelor's degree in Computer Science, Electrical Engineering, Maths, Statistics, economics, a related field, or equivalent practical experience.
• Experience with SQL languages (BigQuery, or other columnar database SQL).
• Experience with writing and maintaining ETL scripts which operate on structured and unstructured sources.
• Experience with Coding, Java, Python, or a similar language.

Preferred qualifications:

• Master's degree in Statistics, Computer Science, Engineering, or Business Analytics.
• 5 years of experience with driving development and design of business solutions and infrastructure to build and scale common frameworks.
• Experience with statistical analysis and modeling.
• Experience with source-control and/or DevOps systems and processes.
• Ability to translate analysis results into business recommendations and questions into an analysis framework.
• Ability to solve and own large, complex problems.

About the job

In this role, you will help ensure the data needed to launch high quality hardware and software for Pixel devices can be trusted and accessible by those that need it. You will partner with Data Science, Analyst, and Engineering teams to build and scale durable data products and infrastructure that will enable business teams to make data-driven business decisions. You will be responsible for technology that moves and translates data used for critical, strategic decisions.

In this role, you will also build data infrastructure that can be used by other systems to automate and improve the user experience. You will design and develop dashboards in order to realize the value of the data assets you help develop.

Responsibilities

• Design, develop, and optimize data warehouses and reporting.
• Write extract, transform, and load (ETL) to automate routine data collection and reporting processes using a variety of large-scale distributed data systems.
• Work closely with Software Engineering teams to design and acquire log-level data.
• Write and review end-user documentation and technical documents, requirements and design documents for existing and future data systems, and data standards and policies.
• Build statistical models and present findings to stakeholders. Create and optimize dashboards.