People Analytics Data Engineer

About this opportunity

We are seeking an expert Data Engineer to join our People Analytics Team. The hire will be responsible for expanding and optimizing our data landscape using a unified and scalable architecture. They will help to optimize our relational data structures with good data warehouse design methodology and some data modeling outside of the data warehouse. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our database architects, data analysts, and data scientists on data initiatives and ensure an optimal data delivery architecture consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited about optimizing or re-designing our company’s data architecture to support our next generation of products and data initiatives!
• We believe in trust – we trust each other to do the right things!
• We believe in taking decisions as close to the product and technical expertise as possible.
• We believe in creativity – trying new things and learning from our mistakes.
• We believe in sharing our insights and helping one another to build an even better user plane.
• We truly believe in happiness, we enjoy and feel passionate about what we do and value each other’s technical competence deeply.

What you will do

Proactively drive the vision for BI and Data Warehousing across a product lifecycle and define and execute a plan to achieve that vision.
• Define the processes needed to achieve operational excellence in data management, including data quality, system reliability, and project management.
• Understanding the business requirements for building a new data model or enhancing the existing ones based on new requirements to ensure that the data models are fit.
• Drive a good schema design for scalable, high-performance data models.
• Drive the design, building, and launching of new data models and data pipelines in production. Create and maintain optimal data pipeline architecture.
• Review the design specification with the Solution Architect and the Development team, bringing in outside-in and best practices perspectives to the solution, validating and quality assuring the Data models, and assessing their fit for purpose.
• Bring knowledge, experience, and best practices to data modeling areas such as Slowly Changing Dimension (SCD) so that we can track the history of dimension records.
• Provide standard processes guidance on building normalized and denormalized tables for addressing different use cases such as dashboard development, data science exploration, and other business-centric use cases.