Position: Data Analyst
Company: Provectus
Category: Data Science
Experience required: 3y
English level: upper

Our client is Abstract, a control & collaboration platform for designers and creatives. The platform helps centralize design decisions, feedback, and files in one place to streamline processes in design teams between creatives, visual professionals, and developers. It keeps track of documents, files, and all changes made to any of them. (https://www.abstract.com/)

The Analytics Engineer is responsible for maintaining and improving Abstract’s data stack to support business intelligence users and decision-makers across the company. In this role, the individual will collaborate with stakeholders across the company to understand their needs and leverage technical skills and experience in aggregating and presenting data in order to create robust reports, data products, and business solutions to address those needs.

Responsibilities:

- Design and build full-stack data infrastructure and tooling, from ingestion/logging through ETL, visualization, and delivery.
- Lead the design, development, and maintenance of ongoing metrics, reports, and tools to generate insights on product performance, customer behavior, business performance and forecasting.
- Work with business stakeholders to gather requirements, then collaborate with other Analytics engineers to create reporting and analytic solutions, and write great documentation for clear data governance.
- Be a strong advocate for a culture of process and data-informed decision-making across the whole company.
- Design efficient data structures to support analytics and reporting that scale with company growth.

Requirements:

- Ability to quickly acquire and leverage business knowledge when designing technical solutions.
- Prior experience in a data role working with data warehouses and business intelligence tools at a growing SaaS company.
- Experience building and managing data pipelines on an AWS (or other cloud) stack.
- Strong SQL skills, including SQL for data transformation and data profiling.
- Experience implementing best-practices for data modeling, especially with regards to dimensional modeling for business intelligence.
- Expertise in experimental design and analysis, particularly with messy real-world data.
- Ability to tell the story behind the numbers
- Ability to prioritize a large volume of requests by using a business-driven lens
- Experience with one programming language, preferably Python
- Experience with git and git-based workflows