Data Engineer

Full-time

Hybrid - Gilbert, AZ

Health and Personal Care Retailers

About the position

The Data Engineer will be responsible for building and maintaining enterprise data management infrastructure both on-premises and in the cloud. The Data Engineer will be responsible for orchestrating pipelines using modern data tools/architectures as well as design and engineering of existing transactional and RDBMS processing systems. This position currently follows a hybrid work model. Employees are required to work from the office at least four days per week (Monday - Thursday), with Friday available for remote work, offering a blend of in-person collaboration and flexibility.

Responsibilities

• Develop and maintain data pipelines that extract, transform, and load data into an information and analytics environment
• Develop and maintain datasets in a conventional data warehouse (operational data store, dimensional models)
• Develop and maintain datasets in a modern, cloud-based data warehouse (Redshift, Snowflake, Azure)
• Implement and configure data sets on column oriented (column-store) database management systems
• Assist application development teams during application design and development for highly complex and critical data projects
• Create and enhance analytic and data platforms using tools that enable state of the art, next generation capabilities and applications
• Utilize programming languages like SQL, Java, Spark, Python, with an emphasis in tuning, optimization, and best practices for application developers
• Function as team member in an Agile development environment
• Leverage DevOps techniques and practices like Continuous Integration, Continuous Deployment, Test Automation, Build Automation and Test-Driven Development to enable the rapid delivery of end user capabilities
• Develop data solutions on cloud deployments such as AWS and Azure
• Understand concepts of data ingestion from event driven architectures
• Remain on the cusp of new technologies in Data Engineering, Big Data and Analytics, and Cloud space

Requirements

• Bachelor's degree from an accredited institution or equivalent experience
• 4+ years experience connecting to various data sources and structures: APIs, NoSQL, RDBMS, Blob Storage, Data Lake, etc.
• Knowledge of cloud providers such as AWS, Azure, and Snowflake
• Database systems (SQL and NoSQL)
• ETL tools including SSIS, Glue, and Kinesis Firehose
• Data APIs
• Python, PowerShell
• Experience with multiplatform integration and distributed systems (Kafka)

Nice-to-haves

• Experience with Dev Ops tools such as Azure DevOps and Visual Studio
• Master Data Management (MDM)
• Understanding of data-warehousing and data-modeling techniques
• Advanced level SQL for data transformations, queries & data modeling
• Data Quality tools and processes
• Graph Database Systems including Neo4J
• Cypher Query Language
• Data warehousing solutions
• T-SQL, MDX, and Spark programming languages
• Prior knowledge of modern Cloud based ETL tools such as Matillion or Fivetran