Job title | Data Analytics Engineer |
Contract type: | Contract |
Location | Remote in Europe |
Industry: | |
Workplace type: | Remote |
Reference: | 5662 |
Contact name: | Greg Wade |
City: | Remote in Europe |
Contact email: | greg.wade@signify-tech.com |
Published: | May 19, 2023 1:40 |
Job Description
The Data Analytics Engineer is an integral part of the technology team, responsible for working with data engineering teams to build data models that feed BI and visualization tools and leading the report/application development process. Data is useless without the skills to analyze and understand it, extract insights, and tell stories that resonate with our customers to help them better understand their businesses.
Must Haves:
- Bachelor's Degree in Engineering, Computer Science, Business, or equivalent.
- Substantial related professional experience, preferably working with tools such as PowerBI, Looker, and Tableau (Looker preferred).
- Preferable experience working with data analytics platforms, such as Google Cloud's BigQuery, Looker, Looker ML, Dataproc, etc.
- Strong SQL skills, working with big data sets and integration tools.
- Experience working in modern BI aspects, including cloud data lake solutions and advanced analytics.
- Deep understanding of architectural principles necessary for delivering scalable, extensible, and maintainable high-performance data-driven cloud, web, and/or mobile experiences.
Nice to Haves:
- Looker certification and Looker LookML certification.
- Experience working with machine learning and ML APIs.
- Experience with Python development.
- Experience with data modeling and/or data warehousing.
Responsibilities:
- Work with business stakeholders to understand their data requirements and translate them into technical requirements for data analytics and business intelligence solutions.
- Develop and maintain data models and dashboards using tools such as Looker, PowerBI, and Tableau, with a preference for Looker.
- Implement and configure data analytics platforms for various business use cases, including data modeling, report building, and dashboard creation.
- Design and develop scalable and efficient data models that align with data governance and quality standards.
- Work with data analytics platforms, including BigQuery, Looker, Looker ML, Dataproc, etc.
- Develop and maintain integrations between data analytics tools and other systems, using strong SQL skills to work with big data sets.
- Collaborate with data engineers to ensure the integrity, accuracy, and completeness of data sources used in data analytics and business intelligence solutions.
- Stay up-to-date with the latest data analytics and business intelligence technologies and trends, and provide recommendations for process improvements and enhancements.
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