We are looking for a savvy Data Engineer to join our growing team of analytics experts. The hire will be responsible for building and optimizing our data pipelines and architecture. The Data Engineer will support data analysts and data scientists to build fast, performant systems while ensuring high quality data for the purpose of analytics. They must be business savvy and self-directed with a startup mindset to lead 407ETR’s data in the cloud strategy. 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 data initiatives.
- 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 and AWS ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Advanced working 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.
- Building dev and production environments and productionizing Machine learning models
- 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.
- Proactive approach to maintaining and cleaning data for data sciences.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’.
- Strong project management and organizational skills.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Note: This job description is not intended to be all-inclusive. Employee may perform other related duties as negotiated to meet the ongoing needs of the organization.
Accommodations for disabilities or other grounds protected by human rights legislation are available upon request for candidates taking part in all aspects of the employment selection process.