As Rainforest Alliance we believe in the value of data. We want our organization and our stakeholders to be able to make data-informed decisions. Therefore, it is key that they can access the information they need in an easy, timely and digestible way.
To enable this, we’ve built a Data Analytics Platform (DAP) where we ingest data from multiple sources, integrate and transform it into information to the end users.
The Data Engineer will work closely with the data excellence team, reporting analysts, and business analysts, to build information pipelines. They will review and deliver on data source integration, data sets used for analysis, report layouts, and delivery processes. This will involve requirement analysis, data staging, ETL, data quality and archiving, in order to bring data from internal and external data sources to the intended users. We use Data Virtuality now and are moving towards Azure Data Factory.
The data engineering team is a team with a primary focus on development of data pipelines, and technical components of the DAP. But as a successful data team we also need data and business analysis skills. As a team we do the full cycle from analysis and design to development to testing and maintenance. This means there is also space for people who are more focused on data analysis and design or testing, but we expect some technical background as well.
The candidate should possess most of the technical skills to
- Analyse and clarify requirements with data owners and users
- Understand relational and conceptual information modelling techniques, especially Data Vault and dimensional modelling. Build data pipelines using SQL and scripting languages
- Deliver and test data sets and reports to agreed levels of accuracy and completeness Design and build data warehouse components and quality monitoring solutions Maintain code bases and tools that make up the data analytics environment Understand processes that ensure structured and quality delivery
Responsibilities
- Understand the business requirements and data models from the source systems that feed the DAP
- Develop, maintain and improve the pipelines into the data analytics platform using procedural SQL, ETL, data virtualization, and databases
- Develop, maintain and improve the data connections between data sources and the data analytics platform, using Terraform and Azure tools, together with the data platform engineer
- Follow processes and maintain version control over the code assets within the data analytics platform
- Be an active participant in the sprint planning and goal definition activities within the Data Excellence team
- Review process, architectural, information and data models in collaboration with the Data Architect, Data Engineers, and the rest of the Data Excellence team