We all know every decision should be driven by data. But what about the data you don’t know? For years, the status quo in data aggregation has lacked visibility, moved slowly, and cost too much. Leaving organizations to make critical decisions, day after day, without the whole picture. Premise changes that.
Across 138 countries and counting, our technology connects communities of global smartphone users to source actionable data in real-time, cost- effectively, and with the visibility you need. So leaders inside organizations, non-profit agencies and governments can now make the best decisions under the best conditions.
With Premise, organizations win. And communities win, too. People can earn more from their opinions and discoveries. They can influence their cities for the better. And, unlike other data sourcing methods out there, they can do it all with full transparency that the data they’re gathering is going to an organization that values it, and values them.
We’re growing rapidly, and we’re searching for an energetic and strategic Analytics Engineer in Bogotá, Colombia. You will be part of a team of highly talented individuals and be responsible for owning and maintaining our data transformation pipelines with the highest standards of quality and best practices. You’ll bridge the gap between raw data and business insights, working with both technical and business stakeholders to ensure data reliability and accessibility.

You’ll work in the Customer Solutions team, a group of analysts, data scientists, methodologists, and statisticians who are responsible for turning our raw data into the insights our customers need to make faster, more effective decisions. Responsibilities include:

• Build and maintain data transformation pipelines
• Design and implement efficient data models

• Create and maintain modular SQL transformations that scaleMonitor pipeline performance and optimize when needed

• • Ensure data quality and reliability
• Design and implement data quality checks and automated testing for data transformations
• Create monitoring systems to detect data anomalies
• Develop and maintain data quality metricsImplement data validation rules and error handling
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• Critically evaluate customer data and refine collection strategies

• Perform ongoing analysis of data to uncover issues related to quality, consistency, and/or comprehension of questions and tasks
• Highlight key insights using statistics and other analytically rigorous tools, packaging them for end users in easily digestible language and formatsRecommend concrete suggestions for improvement and work with other teams to implement, tracking their impact and utility over time
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• Translate research and requirements into recurring products

• Work with Product and Data Science teams to prototype new products and capabilities based on your research and/or customer requirements
• Support these teams’ efforts to improve existing data products to better meet customer requirements and/or increase data subscriptions/collection requests