• We are looking for an accomplished Data Engineer to join our quickly growing Analytics team
• 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 right candidate will be excited by the prospect of optimizing or even re-designing our company’s data pipelines to support our next generation of products and data initiatives
• 2-4 years professional Data Engineering and Data warehousing experience
• Extremely strong implementation experience in Python, Parquet, Spark, Azure Databricks, Delta Lake, Databricks Data Warehouse. Databricks workflows, Delta Sharing and Unity Catalog
• SQL development knowledge – Stored procedures, triggers, jobs, indexes, partitioning, pruning etc
• Be able to write/debug complex SQL queries
• ETL/ELT and Data-warehousing techniques and best practices
• Experience building, maintaining, and scaling ETL/ELT processes and infrastructure
• Implementation experience with various data modelling techniques
• Implementation experience working with a BI visualization tool (Sisense is a plus)
• Experience with CI/CD tools (Preferred Gitlab, Jenkins)
• Experience with cloud infrastructure (Azure strongly preferred)
• Experience working in a fast-paced product environment, with an attitude of getting the job done with the least amount of tech debt
• Knowledge of Master Data Management
• Strong communication, negotiating and estimating skills

Desirable

• The hire will be responsible for expanding and improving our data and data pipeline architecture, as well as optimizing data flow and MDM for cross functional teams
• The Data Engineer will support database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery throughout ongoing projects
• They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products
• Design, develop, and operate large scale data pipelines to support internal and external consumers
• Improve and automate internal processes
• Integrate data sources to meet business requirements
• Write robust, maintainable, well documented code