The Data Engineer is focused on understanding the data and analytics needs of the organization and then designing solutions that will fit those needs. Ultimately, the Data Engineer will provide data solutions on complex business problems to be solved with current technologies and data stores, or by proposing new technologies and/or other resources.
The Analytics Data Engineer will:
- Work closely with the analysts in the line of business, empowering them to use this data as they support their business areas
- Translate business logic from legacy systems and non-systematized processes into Alteryx in a quick and accurate manner
- Work with IT to ensure the appropriate raw data sets have been made available for downstream usage
- Deliver value through direct ownership of data engineering, transformation, automation, and back-end visualization setup, as well as client communication deliverables
- Support build-out of big data environments that enable analytics solutions on a variety of big data and analytics platforms (including Redshift, S3, Hive, Oracle, Alteryx, Tableau)
- Create appropriate documentation of solutions, architecture, automation workflows, and operation procedures to ensure future success and empower other users
- Automate end-to-end data validation to maintain accuracy of data sets
One essential part of this role will be determining the key problem that the stakeholder is trying to address, so asking the right questions and being a good listener are essential in this role. You will utilize your knowledge and skills to address business challenges to improve efficiency and decision making, reduce redundancy, and enhance business results. Your ability to effectively manage client expectations is critical as your goal will be to help them on their journey as we strive to mature data, systems, and infrastructure across the organization.
In order to do this effectively, you will need to build strong working relationships with clients as well as with our Information Technology group, a key partner in data and reporting solutions. The data engineer will need to learn and grow continually since the tools and technology will be constantly evolving, the applications will require more advanced techniques over time, the data availability and data models will be in continual state of flux, and more predictive modeling processes will need to be supported in the future.
- 3-5 years of relevant experience with focus on data management, data modeling, information retrieval, and process analysis
- Combined business/technical education with working knowledge of topics such as cloud computing, computer science, and finance
- Demonstrated analytics data manipulation expertise, work stream management skills, and business consulting acumen
- Excellent academic track record / 3.2 GPA desired
- Bachelor’s degree in Management Information Systems, Engineering, Decision Sciences, Business Analytics, or other similar quantitative/technical discipline
- Broad, versatile knowledge of big datalandscape
- Thorough proficiency with data retrieval and manipulation programming languages (SQL, HiveQL, R, Scala, and/or Python)
- Advanced knowledge with self-service analytic/ETL tools, specifically Alteryx Designer/Server but also Talend, Pentaho, Trifacta Wrangler etc.
- Experience with AWS Big Data Stack of technologies (Redshift, S3, Lambda, RDS, Kenesis, Kafka, EMR, DynamoDB, etc.) a plus
- Experience with visualization platforms (e.g., Tableau, Qlikview, PowerBI, D3.js) a plus
- Experience with Oracle ERP systems a plus
- Ability to manage multiple projects and deadlines simultaneously
- Ability to communicate technical concepts to business people, and to explain business concepts to technical resources
- Ability to learn things quickly and work independently
- Attentiveness to details, with the ability to understand the big picture