Fullstack / Data Engineer
For this role as a Fullstack/Data engineer you will be part of a cross-functional Reporting & Analytics web application team ensuring successful, high quality product deployments. We are looking for an energetic, highly motivated, and detail-oriented data engineer to fill this role. This application is in the middle of a modernization, and we are looking for a well-rounded data engineer who "gets it", who thrives in an agile environment, and who doesn't recognize role boundaries, always swarming to get things done.
As a member of this team, you will be:
- Responsible for expanding and optimizing our data and future data pipeline architecture, as well as optimizing data flows and collections for cross-functional teams.
- An experienced data wrangler who enjoys optimizing data systems and building them from the ground up.
- Self-directed and comfortable supporting the data needs of multiple teams, systems, and products.
- Excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of data initiatives.
location: Raleigh, North Carolina
job type: Contract
salary: $41.25 - 51.50 per hour
work hours: 8am to 5pm
education: No Degree Required
- Ability to recommend and implement ways to improve data reliability, efficiency, and quality.
- Able to employ a variety of languages and tools to marry systems together or try to hunt down opportunities to acquire new data from disparate systems
- Ensure current (and future) architecture supports the needs and requirements of all stakeholders
- Develop data set processes for data modeling, mining, and production
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Build & maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and various other technologies.
- Create and maintain optimal data pipeline architecture,
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Work with stakeholders including executive/product/data/design teams to assist with data-related technical issues and support their data infrastructure needs.
- 4+ years experience in a Data Engineering role, preferably within a web app environment
- Strong understanding of both relational data structures and writing complex data analysis queries, as well as non-relational structures and concepts related to BI
- Advanced working SQL knowledge and experience working with relational/non-relational databases, query authoring (SQL) as well as working familiarity with a variety of databases (eg, MS SQL, MySQL, Oracle, MongoDB).
- Experience building and optimizing 'big data' data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
skills: SW/Tool Experience:
- Experience with relational & non-relational databases, including MS SQL & MongoDB
- Experience with data visualization tools: Domo (preferred), Tableau
- Experience with big data tools: Hadoop, Spark, Kafka, etc
- Experience with scripting languages: Python, R, SQL, Scala, etc
- Experience with tooling: Jenkins Pipeline, Git, Docker, OpenShift
- Experience with unit and functional-level automation: Jasmine/Mocha, Selenium, Spock
- Experience in agile scrum/DevOps/DataOps
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.