We are looking for a savvy Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for functional teams. 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 Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
Responsibilities for Data Engineer
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional/non-functional business requirements
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL
- Work with data and analytics experts to strive for greater functionality in our data systems
Qualifications for Data Engineer
- We are looking for a candidate with 3-5 years of experience in a Data Engineer role, who has attained a Bachelors/Masters degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- Very good analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
- Experience with relational SQL and NoSQL databases
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.