Data Engineer primary focus on expanding and optimizing our data, data pipeline architecture, data flow and collection for multi-functional teams. The Data Engineer will be an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. You will support our software developers, data analysts and data scientists on data initiatives and will ensure efficient data delivery architecture is consistent throughout ongoing projects. You must be proactive and comfortable supporting the data needs of multiple teams, systems and products. You 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. This team is a group of innovators and technologists that love to learn and collaborate! Main Responsibilities:
- Build and maintain optimal data pipeline architecture
- Assemble large, sophisticated 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 efficient extraction, transformation, and loading of data from a wide variety of data sources
- Assist with data-related technical issues and support their data infrastructure needs.
- Build data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics specialists to strive for greater functionality in our data systems.
- Bachelor's degree or higher degree in Computer Science, Statistics, Informatics, Information Systems or related work experience.
- 5+ years of experience in a Data Engineer role
- SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- 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 find 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.
- Experience supporting and working with multi-functional teams in a dynamic environment.
- Experience with relational SQL and NoSQL databases: MongoDB, Neo4j, etc
- Experience with cloud services: Google Cloud Platform, AWS, etc
- Experience with object-oriented/object function scripting languages: Python, Java, etc.
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with Data Flow, Data Pipeline and workflow management tools: Cloud Composer, Airflow, Luigi, etc.