A client in the Colorado area is looking for a Sr Databricks Engineer to join their team. This role will be hybrid, with 3 days max in office each week. The Databricks Engineer will be responsible for Azure Analytics solutions, data pipeline management, databricks solutions, cross functional collaboration and best-practice implementation. You will develop/implement scalable analytic solutions within Azure, design/develop/manage end-to-end pipelines for efficient data collection and storage, work with Delta Lade/data warehouses/datamarts to create analytic solutions, and work across teams to align data solutions. This role will report to the Chief Software Architect and will lean heavily on expertise in data architecture on Databricks delta lake, streaming technologies, Azure cloud platform, ETL development, data modeling, and data warehousing.
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- Bachelors Degree in Computer Science, Engineering, related field OR Substitute years of experience
- 6+ years of experience within the Data Engineering field, with a strong focus in Azure environment
- 4+ years of experience within Data Lake and DataMart Development with a demonstrated proficiency in designing/implementing scalable data architectures
- 4+ years of experience developing data lakes/DataMart within the databricks platform, with an emphasis on Azure Databricks and related Azure Services
- Track record of significantly improving data processing performance and ability to develop/optimize complex data ingestion processes
- Demonstrated expertise in programming languages such as Python, Spark, and SQL
- In-Depth understanding of Apache Spark
- Advanced proficiency in SQL and an understanding of data modeling techniques (Star Schemas)
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.