As a Data Engineer on the Data Integration team your primary focus is to design and build durable data pipelines. You will be working on data integration processes to enable our growing Business Intelligence and Data Science teams. You will work both on-premise and in the cloud with a focus on modernizing our data pipelines and integration strategy to increase data accuracy and availability, lower support cost, and increase speed to shelf. We are looking for people who can be great individual contributors who are also open to pair programming and have a willingness to learn and work with new technologies.
· Build performant and scalable data pipelines
· Create, monitor, and maintain data pipelines
· Ensures new and existing code meets company standards for readability, testability, automation, documentation and performance
· Pair with other team members to increase efficiency and collaboration
· Continually bring features from conception to production, leveraging a DevOps mindset
· Integrate with both existing legacy systems and new modern systems
· Provide after hours on-call support on a rotational basis
KNOWLEDGE, SKILLS AND EXPERIENCE
· Proficient with a programming language (Python)
· Proficient with SQL
· Experience designing, modeling, and implementing snowflake, star, and relational data models.
· Experience using ETL/ELT tools (e.g. SSIS, Informatica) and best practices
· Ability to independently troubleshoot issues, think critically, and clearly communicate findings/recommendations
· Experience using workflow management/orchestration tools (Airflow)
· Experience working on stream-processing systems (Google Pub/Sub, Kafka, etc.)
· Experience using CI/CD technologies (Concourse, Jenkins, Travis CI, etc.)
· Experience building containerized applications (Kubernetes, Docker, etc.)
· Experience with streaming analytics (e.g. Spark, Google Dataflow, Azure Streaming Analytics, etc.)
· Knowledge of cloud databases (e.g. Azure Synapse, Google BigQuery, Snowflake, etc.)
· Experience ingesting data via API's
· Experience with centralizing data from disparate sources, transforming data, and resolving data conflicts Requirements
Azure SQL Database, Google Cloud Platform, Application Integration, Continuous Integration / Continuous Delivery (CICD), BigSQL, ETL-SSIS
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