Senior Analytics Engineer

Here’s How You Make an Impact:

• You are obsessed with building a strong analytics workflow. You will develop efficient, reusable and reliable data models that others depend on to create business and customer value.
• You are an expert in your craft with a depth of knowledge and experience using dbt to transform data from staging to reusable dimensional marts. You will work within dbt Cloud and with Amazon Redshift.
• You will partner with analysts and other stakeholders to understand business needs, document source-to-target mappings, design and document data models, and ensure the output is accepted by stakeholders.
• You will implement validation rules and conduct audits of data models, enforcing governance standards that promote the proper use of data assets. You’ll help to develop data quality tests and documentation to support ongoing data modeling work.
• You’ll help to guide and mentor others, sharing your expertise in data modeling with the goal of improving data literacy across Wave.
• You’ll design and implement processes and tools that drive data-driven decisions across Wave. Your work will mean something and have an impact for the company, empowering teams to make smarter business decisions.

These will help you succeed:

• At least 3 years of experience in Analytics Engineering (or Business Intelligence), particularly data modeling, transformation and data engineering. This is important because this is what you’ll be doing most of the time, and we need someone experienced to do it.
• Must be proficient in dbt.  dbt is our transformation tool for SQL models.
• At least 2 years of experience working with cloud infrastructure, including container development with Kubernetes, GitOps or other infrastructure automation. We work on AWS.
• Experience using dbt to implement an automated data transformation layer in a modern data warehouse, (ideally using the Data Vault 2.0 methodology) running on Redshift.
• Comfortable coding in Python. You’re able to read, update, and maintain code that powers our data pipelines.

You Thrive Here By Possessing the Following:

• At least 5 years of experience in Analytics Engineering, particularly in data modelling and transformation. 
• Strong experience designing and implementing scalable and efficient dimensional data models.
• Proficient in dbt. This includes developing in dbt, as well as dbt project structuring, developing and testing models, leveraging popular packages, and adhering to best practices.
• Experience writing SQL optimized for large and complex datasets. Comfortable coding in Python. You’re able to read, update, and maintain code that powers the AWS Glue jobs in our data lake and pipelines.
• Experience with BI tools, preferably Looker. Experience developing a semantic layer.
• Comfortable using version control systems like Git and CI/CD workflows.
• Practical knowledge of data warehouse design frameworks (e.g., Kimball, data mesh) and best practices, with the ability to coach team members on these concepts.
• You are all about collaboration. You’ll be working with different teams across Wave who have different perspectives and data needs.
• You are a stellar communicator. This means you know how to translate technical terms into non-technical language which your grandma could understand.
• You’re self-motivated and have the ability to work autonomously. We count on you to get your work done and produce high-quality work.
• You value personal and team development. You enjoy helping your team to identify the most important aspects of engineering and best practices.