Data drives All Web Leads' success. AWL’s Technology team is looking for a Data Warehouse Engineer to play a pivotal role in building and deploying systems that allow the entire company to access and utilize the data that enables AWL’s success. In this role, you will collaborate with a multidisciplinary team of engineers, product managers, business intelligence analysts, online marketers, and sales managers on a wide range of data-driven solutions that will shape the future of our company.
As an AWL Data Warehouse Engineer, you will be accountable for the performance, stability, and integrity of our data warehouses and OLAP cubes. Our business is fueled by the customer, web traffic, click stream, and calculated measures data that reside in and are accessed via these systems.
All Web Leads, Inc. (AWL) is one of the most successful online lead generation providers to the US Insurance industry. Our amazing team of extremely talented and successful individuals uses internet marketing to turn consumer interest in insurance products into policy sales for many of the largest insurance carriers (and their agents) in the world. Our growth over the past several years has been remarkable. We’ve been recognized by the Austin Business Journal as one of their “Fast 50" fastest growing private companies in Central Texas for the third consecutive year. We are a tight-knit team with a fast paced, energetic, and entrepreneurial company culture. We are highly profitable and Austin-based. We provide competitive pay, excellent benefits, and a fun and collaborative work environment.
Responsibilities will include:
- Working closely with system owners, BI analysts, and revenue/profit owners across all parts of the company.
- Leading projects and collaborating with others on requirements and product deliverables.
- Architecting OLAP cubes for reporting and processing purposes.
- Analyzing data anomalies and performing root cause analysis.
- Monitoring, managing, and maintaining AWL’s databases such that performance meets expectations.
- Implementing automated data quality checks and monitoring.
- Educating the BI and engineering teams on data domain knowledge and best practices for querying data sets.
- Working with developers to drive best practices for efficient database and OLAP performance